scholarly journals The differential immune responses to COVID-19 in peripheral and lung revealed by single-cell RNA sequencing

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Gang Xu ◽  
Furong Qi ◽  
Hanjie Li ◽  
Qianting Yang ◽  
Haiyan Wang ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Immune Cell ◽  
Close Association ◽  
T Cell Subsets ◽  
Peripheral T Cells ◽  
Single Cell Rna Sequencing

Abstract Understanding the mechanism that leads to immune dysfunction in severe coronavirus disease 2019 (COVID-19) is crucial for the development of effective treatment. Here, using single-cell RNA sequencing, we characterized the peripheral blood mononuclear cells (PBMCs) from uninfected controls and COVID-19 patients and cells in paired broncho-alveolar lavage fluid (BALF). We found a close association of decreased dendritic cells (DCs) and increased monocytes resembling myeloid-derived suppressor cells (MDSCs), which correlated with lymphopenia and inflammation in the blood of severe COVID-19 patients. Those MDSC-like monocytes were immune-paralyzed. In contrast, monocyte-macrophages in BALFs of COVID-19 patients produced massive amounts of cytokines and chemokines, but secreted little interferons. The frequencies of peripheral T cells and NK cells were significantly decreased in severe COVID-19 patients, especially for innate-like T and various CD8+ T cell subsets, compared to healthy controls. In contrast, the proportions of various activated CD4+ T cell subsets among the T cell compartment, including Th1, Th2, and Th17-like cells were increased and more clonally expanded in severe COVID-19 patients. Patients’ peripheral T cells showed no sign of exhaustion or augmented cell death, whereas T cells in BALFs produced higher levels of IFNG, TNF, CCL4, CCL5, etc. Paired TCR tracking indicated abundant recruitment of peripheral T cells to the severe patients’ lung. Together, this study comprehensively depicts how the immune cell landscape is perturbed in severe COVID-19.

scholarly journals The differential immune responses to COVID-19 in peripheral and lung revealed by single-cell RNA sequencing

2020 ◽  
Author(s):  
Gang Xu ◽  
Furong Qi ◽  
Hanjie Li ◽  
Qianting Yang ◽  
Haiyan Wang ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Mononuclear Cells ◽  
Immune Cell ◽  
Close Association ◽  
Suppressor Cells ◽  
T Cell Subsets ◽  
Peripheral Blood Mononuclear ◽  
Peripheral T Cells

Understanding the mechanism that leads to immune dysfunction induced by SARS-CoV2 virus is crucial to develop treatment for severe COVID-19. Here, using single cell RNA-seq, we characterized the peripheral blood mononuclear cells (PBMC) from uninfected controls and COVID-19 patients, and cells in paired broncho-alveolar lavage fluid (BALF). We found a close association of decreased dendritic cells (DC) and increased monocytes resembling myeloid-derived suppressor cells (MDSC) which correlated with lymphopenia and inflammation in the blood of severe COVID-19 patients. Those MDSC-like monocytes were immune-paralyzed. In contrast, monocyte-macrophages in BALFs of COVID-19 patients produced massive amounts of cytokines and chemokines, but secreted little interferons. The frequencies of peripheral T cells and NK cells were significantly decreased in severe COVID-19 patients, especially for innate-like T and various CD8+ T cell subsets, compared to health controls. In contrast, the proportions of various activated CD4+ T cell subsets, including Th1, Th2 and Th17-like cells were increased and more clonally expanded in severe COVID-19 patients. Patients' peripheral T cells showed no sign of exhaustion or augmented cell death, whereas T cells in BALFs produced higher levels of IFNG, TNF, CCL4 and CCL5 etc. Paired TCR tracking indicated abundant recruitment of peripheral T cells to the patients' lung. Together, this study comprehensively depicts how the immune cell landscape is perturbed in severe COVID-19.

scholarly journals Re-investigation of classic T cell subsets and identification of novel cell subpopulations by single-cell RNA sequencing

2021 ◽  
Author(s):  
Xuefei Wang ◽  
Xiangru Shen ◽  
Shan Chen ◽  
Hongyi Liu ◽  
Ni Hong ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Cell Surface ◽  
Single Cell ◽  
Rna Sequencing ◽  
T Cell Activation ◽  
Expression Profiles ◽  
T Cell Subsets ◽  
Cell Subpopulation ◽  
Single Cell Rna Sequencing

AbstractClassic T cell subsets are defined by a small set of cell surface markers, while single cell RNA sequencing (scRNA-seq) clusters cells using genome-wide gene expression profiles. The relationship between scRNA-seq Clustered-Populations (scCPops) and cell surface marker-defined classic T cell subsets remain unclear. Here, we interrogated 6 bead-enriched T cell subsets with 62,235 single cell transcriptomes and re-grouped them into 9 scCPops. Bead-enriched CD4 Naïve and CD8 Naïve were mainly clustered into their scCPop counterparts, while cells from the other T cell subsets were assigned to multiple scCPops including mucosal-associated invariant T cells and natural killer T cells. The multiple T cell subsets that form a single scCPop exhibited similar expression pattern, but not vice versa, indicating scCPops are much homogeneous cell populations with similar cell states. Interestingly, we discovered and named IFNhi T, a new T cell subpopulation that highly expressed Interferon Signaling Associated Genes (ISAGs). We further enriched IFNhi T by FACS sorting of BST2 for scRNA-seq analyses. IFNhi T cluster disappeared on tSNE plot after removing ISAGs, while IFNhi T cluster showed up by tSNE analyses of ISAGs alone, indicating ISAGs are the major contributor of IFNhi T cluster. BST2+ T cells and BST2− T cells showing different efficiencies of T cell activation indicates high level of ISAGs may contribute to quick immune responses.

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 Global immune characterization of HBV/HCV-related hepatocellular carcinoma identifies macrophage and T-cell subsets associated with disease progression

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Guohe Song ◽  
Yang Shi ◽  
Meiying Zhang ◽  
Shyamal Goswami ◽  
Saifullah Afridi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
T Cell Subsets ◽  
M2 Macrophage ◽  
Advanced Hcc ◽  
Immune Cell Subsets

AbstractDiverse immune cells in the tumor microenvironment form a complex ecosystem, but our knowledge of their heterogeneity and dynamics within hepatocellular carcinoma (HCC) still remains limited. To assess the plasticity and phenotypes of immune cells within HBV/HCV-related HCC microenvironment at single-cell level, we performed single-cell RNA sequencing on 41,698 immune cells from seven pairs of HBV/HCV-related HCC tumors and non-tumor liver tissues. We combined bio-informatic analyses, flow cytometry, and multiplex immunohistochemistry to assess the heterogeneity of different immune cell subsets in functional characteristics, transcriptional regulation, phenotypic switching, and interactions. We identified 29 immune cell subsets of myeloid cells, NK cells, and lymphocytes with unique transcriptomic profiles in HCC. A highly complex immunological network was shaped by diverse immune cell subsets that can transit among different states and mutually interact. Notably, we identified a subset of M2 macrophage with high expression of CCL18 and transcription factor CREM that was enriched in advanced HCC patients, and potentially participated in tumor progression. We also detected a new subset of activated CD8+ T cells highly expressing XCL1 that correlated with better patient survival rates. Meanwhile, distinct transcriptomic signatures, cytotoxic phenotypes, and evolution trajectory of effector CD8+ T cells from early-stage to advanced HCC were also identified. Our study provides insight into the immune microenvironment in HBV/HCV-related HCC and highlights novel macrophage and T-cell subsets that could be further exploited in future immunotherapy.

scholarly journals Heterogeneity of T Cells in Atherosclerosis Defined by Single-Cell RNA-Sequencing and Cytometry by Time of Flight

2020 ◽  
Author(s):  
Holger Winkels ◽  
Dennis Wolf
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
T Regulatory Cells ◽  
Foam Cell ◽  
Regulatory Cells ◽  
T Helper ◽  
Antigen Specificity ◽  
Single Cell Rna Sequencing

The infiltration and accumulation of pro- and anti-inflammatory leukocytes within the intimal layer of the arterial wall is a hallmark of developing and progressing atherosclerosis. While traditionally perceived as macrophage- and foam cell-dominated disease, it is now established that atherosclerosis is a partial autoimmune disease that involves the recognition of peptides from ApoB (apolipoprotein B), the core protein of LDL (low-density lipoprotein) cholesterol particles, by CD4 + T-helper cells and autoantibodies against LDL and ApoB. Autoimmunity in the atherosclerotic plaque has long been understood as a pathogenic T-helper type-1 driven response with proinflammatory cytokine secretion. Recent developments in high-parametric cell immunophenotyping by mass cytometry, single-cell RNA-sequencing, and in tools exploring antigen-specificity have established the existence of several unforeseen layers of T cell diversity with mixed T H 1 and T regulatory cells transcriptional programs and unpredicted fates. These findings suggest that pathogenic ApoB-reactive T cells evolve from atheroprotective and immunosuppressive CD4 + T regulatory cells that lose their protective properties over time. Here, we discuss T cell heterogeneity in atherosclerosis with a focus on plasticity, antigen-specificity, exhaustion, maturation, tissue residency, and its potential use in clinical prediction.

scholarly journals Reclassification of classic T cell subsets and identification of novel cell types by single-cell RNA sequencing

2020 ◽  
Author(s):  
Xiangru Shen ◽  
Xuefei Wang ◽  
Shan Chen ◽  
Hongyi Liu ◽  
Ni Hong ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
T Cell Activation ◽  
Cell Activation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
T Cell Subsets ◽  
Single Cell Rna Sequencing

Abstract Single cell RNA sequencing (scRNA-seq) clusters cells using genome-wide gene expression profiles. The relationship between scRNA-seq Clustered-Populations (scCPops) and cell surface marker-defined classic T cell subsets is unclear. Here, we interrogated 6 bead-enriched T cell subsets with 62,235 single cell transcriptomes and re-grouped them into 9 scCPops. Bead-enriched CD4 Naïve, CD8 Naïve and CD4 memory were mainly clustered into their scCPop counterparts, while the other T cell subsets were clustered into multiple scCPops including unexpected mucosal-associated invariant T cell and natural killer T cell. Most interestingly, we discovered a new T cell type that highly expressed Interferon Signaling Associated Genes (ISAGs), namely IFNhi T. We further enriched IFNhi T for scRNA-seq analyses. IFNhi T cluster disappeared on tSNE after removing ISAGs, and IFNhi T cluster showed up by tSNE analyses of ISAGs alone, indicating ISAGs are the major contributor of IFNhi T cluster. BST2+ cells and BST2- cells showing different efficiencies of T cell activation indicates high ISAGs may contribute to quick immune responses.

scholarly journals OMIC-11. SINGLE CELL RNA SEQUENCING FROM THE CSF OF SUBJECTS WITH H3K27M+ DIPG/DMG TREATED WITH GD2 CAR T-CELLULAR THERAPY

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i39-i39
Author(s):  
Aaron Mochizuki ◽  
Sneha Ramakrishna ◽  
Zina Good ◽  
Shabnum Patel ◽  
Harshini Chinnasamy ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Product ◽  
Myeloid Suppressor Cells ◽  
Car T Cells ◽  
Car T Cell ◽  
Car T ◽  
Single Cell Rna Sequencing

Abstract Introduction We are conducting a Phase I clinical trial utilizing chimeric antigen receptor (CAR) T-cells targeting GD2 (NCT04196413) for H3K27M-mutant diffuse intrinsic pontine glioma (DIPG) and spinal cord diffuse midline glioma (DMG). Cerebrospinal fluid (CSF) is collected for correlative studies at the time of routine intracranial pressure monitoring via Ommaya catheter. Here we present single cell RNA-sequencing results from the first 3 subjects. Methods Single cell RNA-sequencing was performed utilizing 10X Genomics on cells isolated from CSF at various time points before and after CAR T-cell administration and on the CAR T-cell product. Output was aligned with Cell Ranger and analyzed in R. Results As detailed in the Majzner et al. abstract presented at this meeting, three of four subjects treated at dose-level one exhibited clear radiographic and/or clinical benefit. We have to date completed single cell RNA-sequencing for three of these four subjects (two with benefit, one without). After filtering out low-quality signals and doublets, 89,604 cells across 3 subjects were analyzed. Of these, 4,122 cells represent cells isolated from CSF and 85,482 cells represent CAR T-cell product. Two subjects who demonstrated clear clinical and radiographic improvement exhibited fewer S100A8+S100A9+ myeloid suppressor-cells and CD25+FOXP3+ regulatory T-cells in the CSF pre-infusion compared to the subject who did not derive a therapeutic response. In one subject with DIPG who demonstrated improvement, polyclonal CAR T-cells detectable in CSF at Day +14 demonstrated enrichment of CD8A, GZMA, GNLY and PDCD1 compared to the pre-infusion CAR T-cells by trajectory analysis, suggesting differentiation toward a cytotoxic phenotype; the same subject exhibited increasing numbers of S100A8+S100A9+ myeloid cells and CX3CR1+P2RY12+ microglia over time. Further analyses will be presented as data become available. Conclusions The presence of immunosuppressive myeloid populations, detectable in CSF, may correlate to clinical response in CAR T cell therapy for DIPG/DMG.

scholarly journals Targeted reconstruction of T cell receptor sequence from single cell RNA-sequencing links CDR3 length to T cell differentiation state

2016 ◽  
Author(s):  
Shaked Afik ◽  
Kathleen B. Yates ◽  
Kevin Bi ◽  
Samuel Darko ◽  
Jernej Godec ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Response ◽  
T Cell Response ◽  
Effector Memory ◽  
Cell State ◽  
Tcr Repertoire ◽  
Single Cell Rna Sequencing

ABSTRACTThe T cell compartment must contain diversity in both TCR repertoire and cell state to provide effective immunity against pathogens1,2. However, it remains unclear how differences in the TCR contribute to heterogeneity in T cell state at the single cell level because most analysis of the TCR repertoire has, to date, aggregated information from populations of cells. Single cell RNA-sequencing (scRNA-seq) can allow simultaneous measurement of TCR sequence and global transcriptional profile from single cells. However, current protocols to directly sequence the TCR require the use of long sequencing reads, increasing the cost and decreasing the number of cells that can be feasibly analyzed. Here we present a tool that can efficiently extract TCR sequence information from standard, short-read scRNA-seq libraries of T cells: TCR Reconstruction Algorithm for Paired-End Single cell (TRAPeS). We apply it to investigate heterogeneity in the CD8+T cell response in humans and mice, and show that it is accurate and more sensitive than previous approaches3,4. We applied TRAPeS to single cell RNA-seq of CD8+T cells specific for a single epitope from Yellow Fever Virus5. We show that the recently-described "naive-like" memory population of YFV-specific CD8+T cells have significantly longer CDR3 regions and greater divergence from germline sequence than do effector-memory phenotype CD8+T cells specific for YFV. This suggests that TCR usage contributes to heterogeneity in the differentiation state of the CD8+T cell response to YFV. TRAPeS is publicly available, and can be readily used to investigate the relationship between the TCR repertoire and cellular phenotype.

scholarly journals STARTRAC analyses of scRNAseq data from tumor models reveal T cell dynamics and therapeutic targets

2021 ◽  
Vol 218 (6) ◽  
Author(s):  
Dev Bhatt ◽  
Boxi Kang ◽  
Deepali Sawant ◽  
Liangtao Zheng ◽  
Kristy Perez ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Target Genes ◽  
Cellular Heterogeneity ◽  
T Cell Subsets ◽  
Mouse Tumor ◽  
Tumor Models ◽  
Antibody Treatment ◽  
Single Cell Rna Sequencing

Single-cell RNA sequencing is a powerful tool to examine cellular heterogeneity, novel markers and target genes, and therapeutic mechanisms in human cancers and animal models. Here, we analyzed single-cell RNA sequencing data of T cells obtained from multiple mouse tumor models by PCA-based subclustering coupled with TCR tracking using the STARTRAC algorithm. This approach revealed various differentiated T cell subsets and activation states, and a correspondence of T cell subsets between human and mouse tumors. STARTRAC analyses demonstrated peripheral T cell subsets that were developmentally connected with tumor-infiltrating CD8+ cells, CD4+ Th1 cells, and T reg cells. In addition, large amounts of paired TCRα/β sequences enabled us to identify a specific enrichment of paired public TCR clones in tumor. Finally, we identified CCR8 as a tumor-associated T reg cell marker that could preferentially deplete tumor-associated T reg cells. We showed that CCR8-depleting antibody treatment provided therapeutic benefit in CT26 tumors and synergized with anti–PD-1 treatment in MC38 and B16F10 tumor models.

scholarly journals VirtualCytometry: a webserver for evaluating immune cell differentiation using single-cell RNA sequencing data

2019 ◽  
Vol 36 (2) ◽  
pp. 546-551 ◽  
Author(s):  
Kyungsoo Kim ◽  
Sunmo Yang ◽  
Sang-Jun Ha ◽  
Insuk Lee
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Cell Differentiation ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Signaling Molecules ◽  
Single Cell Rna Sequencing ◽  
Functional States

Abstract Motivation The immune system has diverse types of cells that are differentiated or activated via various signaling pathways and transcriptional regulation upon challenging conditions. Immunophenotyping by flow and mass cytometry are the major approaches for identifying key signaling molecules and transcription factors directing the transition between the functional states of immune cells. However, few proteins can be evaluated by flow cytometry in a single experiment, preventing researchers from obtaining a comprehensive picture of the molecular programs involved in immune cell differentiation. Recent advances in single-cell RNA sequencing (scRNA-seq) have enabled unbiased genome-wide quantification of gene expression in individual cells on a large scale, providing a new and versatile analytical pipeline for studying immune cell differentiation. Results We present VirtualCytometry, a web-based computational pipeline for evaluating immune cell differentiation by exploiting cell-to-cell variation in gene expression with scRNA-seq data. Differentiating cells often show a continuous spectrum of cellular states rather than distinct populations. VirtualCytometry enables the identification of cellular subsets for different functional states of differentiation based on the expression of marker genes. Case studies have highlighted the usefulness of this subset analysis strategy for discovering signaling molecules and transcription factors for human T-cell exhaustion, a state of T-cell dysfunction, in tumor and mouse dendritic cells activated by pathogens. With more than 226 scRNA-seq datasets precompiled from public repositories covering diverse mouse and human immune cell types in normal and disease tissues, VirtualCytometry is a useful resource for the molecular dissection of immune cell differentiation. Availability and implementation www.grnpedia.org/cytometry

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