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

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.

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

Nature Communications ◽

10.1038/s41467-019-11257-y ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 11

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 ◽

Human Immune

Integrative single cell RNA-sequencing descrambles a substantial divergence of adaptive immune cell identities and transcriptional programs in mouse and human atherosclerosis

European Heart Journal ◽

10.1093/eurheartj/ehab724.3411 ◽

2021 ◽

Vol 42 (Supplement_1) ◽

Author(s):

H Horstmann ◽

N Anto Michel ◽

X S Sheng ◽

S Hansen ◽

A Lindau ◽

...

Keyword(s):

T Cell ◽

Single Cell ◽

Rna Sequencing ◽

Immune Cells ◽

Immune Cell ◽

Atherosclerotic Plaques ◽

Cell Repertoire ◽

Human Atherosclerosis ◽

Human Immune

Abstract Aims The distinct function of immune cells in human atherosclerosis has been mostly defined by preclinical mouse studies. Contrastingly, the immune cell composition of human atherosclerotic plaques and their contribution to disease progression is only poorly understood. It remains uncertain whether genetic animal models allow for valuable translational approaches. Methods and results We performed single cell RNA-sequencing (scRNAseq) to define the immune cell landscape in human carotid atherosclerotic plaques. The human immune cell repertoire was dominated by T cells with a considerable inter-patient variability and an unexpected heterogeneity. We performed bioinformatical integration with 7 mouse data sets and discovered a total of 38 cellular identities, of which some were not conserved between species and exclusively found in mice or humans. Locations, frequencies, and transcriptional programs of immune cells in preclinical mouse models did not resemble the immune cell landscape in human atherosclerosis. In contrast to mice, human plaques were not myeloid- and B cell-dominated and instead contained several T cell phenotypes with hallmarks of T cell memory, dysregulation, exhaustion, and activation. Human immune cells were predominantly enriched for transcriptional programs of hypoxia, glucose, and autoimmunity. In a validation cohort of 43 patients activated immune cell subsets defined by multi-colour flow cytometry associated with cerebral ischemia and coronary artery disease. Conclusion Here, we uncover yet undefined immune cell types associating with clinical disease. This leukocyte atlas of human atherosclerosis builds the conceptual basis for subsequent identification of cellular targets for clinical immunomodulatory therapies and risk prediction. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): ERC Starting Grant

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

Cell & Bioscience ◽

10.1186/s13578-021-00613-5 ◽

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 ◽

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.

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

STAR Protocols ◽

10.1016/j.xpro.2021.100582 ◽

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 ◽

Demuxalot: scaled up genetic demultiplexing for single-cell sequencing

10.1101/2021.05.22.443646 ◽

2021 ◽

Author(s):

Alex Rogozhnikov ◽

Pavan Ramkumar ◽

Saul Kato ◽

Sean Escola

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Single Cell Sequencing ◽

Additional Information ◽

Genotype Information ◽

Genotype Inference

Demultiplexing methods have facilitated the widespread use of single-cell RNA sequencing (scRNAseq) experiments by lowering costs and reducing technical variations. Here, we present demuxalot: a method for probabilistic genotype inference from aligned reads, with no assumptions about allele ratios and efficient incorporation of prior genotype information from historical experiments in a multi-batch setting. Our method efficiently incorporates additional information across reads originating from the same transcript, enabling up to 3x more calls per read relative to naive approaches. We also propose a novel and highly performant tradeoff between methods that rely on reference genotypes and methods that learn variants from the data, by selecting a small number of highly informative variants that maximize the marginal information with respect to reference single nucleotide variants (SNVs). Our resulting improved SNV-based demultiplex method is up to 3x faster, 3x more data efficient, and achieves significantly more accurate doublet discrimination than previously published methods. This approach renders scRNAseq feasible for the kind of large multi-batch, multi-donor studies that are required to prosecute diseases with heterogeneous genetic backgrounds.

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

Aging ◽

10.18632/aging.102774 ◽

2020 ◽

Vol 12 (3) ◽

pp. 2747-2763 ◽

Cited By ~ 2

Author(s):

Kai Fu ◽

Bingqing Hui ◽

Qian Wang ◽

Chen Lu ◽

Weihong Shi ◽

...

Keyword(s):

Gastric Cancer ◽

Single Cell ◽

Cancer Patients ◽

Rna Sequencing ◽

Immune Cells ◽

Gastric Cancer Patients

Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses

Biochemical and Biophysical Research Communications ◽

10.1016/j.bbrc.2020.03.044 ◽

2020 ◽

Vol 526 (1) ◽

pp. 135-140 ◽

Cited By ~ 228

Author(s):

Furong Qi ◽

Shen Qian ◽

Shuye Zhang ◽

Zheng Zhang

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Cell Types ◽

Human Tissues ◽

Human Coronaviruses

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

Circulation Research ◽

10.1161/circresaha.120.317104 ◽

2020 ◽

Cited By ~ 1

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 ◽

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.

PRIME: a probabilistic imputation method to reduce dropout effects in single-cell RNA sequencing

Bioinformatics ◽

10.1093/bioinformatics/btaa278 ◽

2020 ◽

Vol 36 (13) ◽

pp. 4021-4029

Author(s):

Hyundoo Jeong ◽

Zhandong Liu

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

Expression Profiles ◽

Expression Patterns ◽

Imputation Method ◽

Supplementary Information ◽

Single Cell Sequencing ◽

Depth Analysis ◽

Abstract Summary Single-cell RNA sequencing technology provides a novel means to analyze the transcriptomic profiles of individual cells. The technique is vulnerable, however, to a type of noise called dropout effects, which lead to zero-inflated distributions in the transcriptome profile and reduce the reliability of the results. Single-cell RNA sequencing data, therefore, need to be carefully processed before in-depth analysis. Here, we describe a novel imputation method that reduces dropout effects in single-cell sequencing. We construct a cell correspondence network and adjust gene expression estimates based on transcriptome profiles for the local subnetwork of cells of the same type. We comprehensively evaluated this method, called PRIME (PRobabilistic IMputation to reduce dropout effects in Expression profiles of single-cell sequencing), on synthetic and eight real single-cell sequencing datasets and verified that it improves the quality of visualization and accuracy of clustering analysis and can discover gene expression patterns hidden by noise. Availability and implementation The source code for the proposed method is freely available at https://github.com/hyundoo/PRIME. Supplementary information Supplementary data are available at Bioinformatics online.

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

Cardiovascular Research ◽

10.1093/cvr/cvaa101 ◽

2020 ◽

Cited By ~ 3

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 ◽

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.