scholarly journals Interpretation of T cell states from single-cell transcriptomics data using reference atlases

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Massimo Andreatta ◽  
Jesus Corria-Osorio ◽  
Sören Müller ◽  
Rafael Cubas ◽  
George Coukos ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Immune Cell ◽  
Meta Analysis ◽  
Single Cell Rna Sequencing ◽  
Cell Diversity ◽  
Transcriptomics Data ◽  
Consistent Basis ◽  
Definition Of ◽  
Human And Mouse

AbstractSingle-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of immune cell diversity. However, consistent definition of cell subtypes and cell states across studies and diseases remains a major challenge. Here we generate reference T cell atlases for cancer and viral infection by multi-study integration, and develop ProjecTILs, an algorithm for reference atlas projection. In contrast to other methods, ProjecTILs allows not only accurate embedding of new scRNA-seq data into a reference without altering its structure, but also characterizing previously unknown cell states that “deviate” from the reference. ProjecTILs accurately predicts the effects of cell perturbations and identifies gene programs that are altered in different conditions and tissues. A meta-analysis of tumor-infiltrating T cells from several cohorts reveals a strong conservation of T cell subtypes between human and mouse, providing a consistent basis to describe T cell heterogeneity across studies, diseases, and species.

scholarly journals Projecting single-cell transcriptomics data onto a reference T cell atlas to interpret immune responses

2020 ◽  
Author(s):  
Massimo Andreatta ◽  
Jesus Corria-Osorio ◽  
Sören Müller ◽  
Rafael Cubas ◽  
George Coukos ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Meta Analysis ◽  
Human Tumor ◽  
Computational Method ◽  
Effector Memory ◽  
Specific Effector ◽  
Transcriptomics Data ◽  
Cancer Types ◽  
Human And Mouse

SummarySingle-cell RNA-sequencing (scRNA-seq) has emerged as a revolutionary technology for characterizing the heterogeneity of cell populations. However, robust reference atlases that can be used to systematically interpret cellular states across studies and diseases are currently lacking. Here, we generated the first cross-study T cell atlases for cancer and viral infection and developed a novel algorithm, ProjecTILs, that enables the projection of new scRNA-seq data onto these reference atlases. ProjecTILs accurately predicted the effects of multiple perturbations, including the ablation of immunoregulatory targets controlling T cell differentiation, such as Tox, Ptpn2, miR-155 and Regnase-1, and suggested novel gene programs that were altered in these cells. Moving beyond mouse models, we used ProjecTILs to conduct a meta-analysis of human tumor-infiltrating T lymphocytes (TILs), revealing a remarkable conservation of TIL subtypes between human and mouse and across cancer types. Clonotype analysis supported a model in which rare human tumor-specific effector-memory (EM)-like CD8 TILs that resemble blood-circulating EM cells, differentiate into proliferative terminal exhausted/dysfunctional effector TILs through a progenitor subtype that upregulates the exhaustion master regulator TOX. Our novel computational method allows exploring the effect of human and murine T cell perturbations (e.g. as the result of therapy or genetic engineering) in terms of reference cellular states, altered genetic programs and clonotype structure, revealing mechanisms of action behind immunotherapies and opening opportunities for their improvement.

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 Analysis of cell diversity in human and mouse basal ganglia by single-cell RNA sequencing

IBRO Reports ◽  
2019 ◽  
Vol 6 ◽  
pp. S328
Author(s):  
Fengjiao Li ◽  
Mohammad Imam Hasan Bin Asad ◽  
Xiangshan Yuan ◽  
Weiwei Xian ◽  
Qiong Liu ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cell Rna Sequencing ◽  
Cell Diversity ◽  
Human And Mouse

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

scholarly journals Single-Cell Proteomics Study of Immune Cell Diversity by Quantitating 465 Proteins

2022 ◽  
Author(s):  
Liwei Yang ◽  
Jesse Liu ◽  
Revanth Reddy ◽  
Jun Wang
Keyword(s):  
T Cell ◽  
Immune Responses ◽  
Single Cell ◽  
Immune Cell ◽  
Single Cells ◽  
Additional Information ◽  
Sequencing Technologies ◽  
Cell Diversity ◽  
Cell Subpopulations ◽  
T Cell Subpopulations

The identification and characterization of T cell subpopulations is critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced the single-cell genomics and transcriptomics for T cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in the protein format. Current single-cell proteomics technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein we present a cyclic multiplex in situ tagging (Cyclic MIST) technology to simultaneously measure 465 proteins, a scale of >10 times than similar technologies, in single cells. Such a high multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both THP1 and CD4+ T cells are analyzed by the Cyclic MIST technology, and over 300 surface markers have been profiled to classify the subpopulations. This represents the most comprehensive mapping of the diversity of immune cells at the protein level. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses, particularly cytokine storm that results in sepsis.

scholarly journals Mapping the Immune Landscape of Clear Cell Renal Cell Carcinoma by Single-Cell RNA-seq

2019 ◽  
Author(s):  
Ajaykumar Vishwakarma ◽  
Nicholas Bocherding ◽  
Michael S. Chimenti ◽  
Purshottam Vishwakarma ◽  
Kenneth Nepple ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cell ◽  
Single Cell ◽  
T Cell Receptor ◽  
Immune Cells ◽  
Immune Cell ◽  
Clear Cell ◽  
Cell Receptor ◽  
Cell Renal Cell Carcinoma ◽  
Single Cell Rna Sequencing

AbstractThe immune cells within the tumor microenvironment are considered key determinants of response to cancer immunotherapy. Immune checkpoint blockade (ICB) has transformed the treatment of clear cell renal cell carcinoma (ccRCC), although the role of specific immune cell states remains unclear. To characterize the tumor microenvironment (TME) of ccRCC, we applied single-cell RNA sequencing (scRNA-seq) along with paired T cell receptor sequencing to map the transcriptomic heterogeneity of 24,904 individual CD45+ lymphoid and myeloid cells in matched tumor and blood from patients with ccRCC. We identified multiple distinct immune cell phenotypes for B and T (CD4 and CD8) lymphocytes, natural kill (NK) cells, and myeloid cells. Evaluation of T cell receptor (TCR) sequences revealed limited shared clonotypes between patients, whereas tumor-infiltrating T cell clonotypes were frequently found in peripheral blood, albeit in lower abundance. We further show that the circulating CD4+ T cell clonality is far less diverse than peripheral CD8+. Evaluation of myeloid subsets revealed unique gene programs defining monocytes, dendritic cells and tumor-associated macrophages. In summary, here we have leveraged scRNA-seq to refine our understanding of the relative abundance, diversity and complexity of the immune landscape of ccRCC. This report represents the first characterization of ccRCC immune landscape using scRNA-seq. With further characterization and functional validation, these findings may identify novel sub-populations of immune cells amenable to therapeutic intervention.One Sentence SummarySingle-cell RNA-sequencing reveals unique lymphoid and myeloid gene programs with putative functions in clear cell renal cancer patients

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.

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

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 ◽  
Single Cell Rna Sequencing ◽  
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

scholarly journals Melanoma Single-Cell Biology in Experimental and Clinical Settings

2021 ◽  
Vol 10 (3) ◽  
pp. 506
Author(s):  
Hans Binder ◽  
Maria Schmidt ◽  
Henry Loeffler-Wirth ◽  
Lena Suenke Mortensen ◽  
Manfred Kunz
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Intracellular Signaling ◽  
Cell Biology ◽  
Immune Cell ◽  
Malignant Tumors ◽  
Checkpoint Inhibitor ◽  
Treatment Resistance ◽  
Resistance Mechanisms ◽  
Cellular Heterogeneity

Cellular heterogeneity is regarded as a major factor for treatment response and resistance in a variety of malignant tumors, including malignant melanoma. More recent developments of single-cell sequencing technology provided deeper insights into this phenomenon. Single-cell data were used to identify prognostic subtypes of melanoma tumors, with a special emphasis on immune cells and fibroblasts in the tumor microenvironment. Moreover, treatment resistance to checkpoint inhibitor therapy has been shown to be associated with a set of differentially expressed immune cell signatures unraveling new targetable intracellular signaling pathways. Characterization of T cell states under checkpoint inhibitor treatment showed that exhausted CD8+ T cell types in melanoma lesions still have a high proliferative index. Other studies identified treatment resistance mechanisms to targeted treatment against the mutated BRAF serine/threonine protein kinase including repression of the melanoma differentiation gene microphthalmia-associated transcription factor (MITF) and induction of AXL receptor tyrosine kinase. Interestingly, treatment resistance mechanisms not only included selection processes of pre-existing subclones but also transition between different states of gene expression. Taken together, single-cell technology has provided deeper insights into melanoma biology and has put forward our understanding of the role of tumor heterogeneity and transcriptional plasticity, which may impact on innovative clinical trial designs and experimental approaches.

scholarly journals MBRS-46. CHARTING NEOPLASTIC AND IMMUNE CELL HETEROGENEITY IN HUMAN AND GEM MODELS OF MEDULLOBLASTOMA USING scRNAseq

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii406-iii406
Author(s):  
Andrew Donson ◽  
Kent Riemondy ◽  
Sujatha Venkataraman ◽  
Ahmed Gilani ◽  
Bridget Sanford ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Cell Heterogeneity ◽  
Transcriptomic Data ◽  
Single Cell Rna Sequencing ◽  
Transcript Profiles

Abstract We explored cellular heterogeneity in medulloblastoma using single-cell RNA sequencing (scRNAseq), immunohistochemistry and deconvolution of bulk transcriptomic data. Over 45,000 cells from 31 patients from all main subgroups of medulloblastoma (2 WNT, 10 SHH, 9 GP3, 11 GP4 and 1 GP3/4) were clustered using Harmony alignment to identify conserved subpopulations. Each subgroup contained subpopulations exhibiting mitotic, undifferentiated and neuronal differentiated transcript profiles, corroborating other recent medulloblastoma scRNAseq studies. The magnitude of our present study builds on the findings of existing studies, providing further characterization of conserved neoplastic subpopulations, including identification of a photoreceptor-differentiated subpopulation that was predominantly, but not exclusively, found in GP3 medulloblastoma. Deconvolution of MAGIC transcriptomic cohort data showed that neoplastic subpopulations are associated with major and minor subgroup subdivisions, for example, photoreceptor subpopulation cells are more abundant in GP3-alpha. In both GP3 and GP4, higher proportions of undifferentiated subpopulations is associated with shorter survival and conversely, differentiated subpopulation is associated with longer survival. This scRNAseq dataset also afforded unique insights into the immune landscape of medulloblastoma, and revealed an M2-polarized myeloid subpopulation that was restricted to SHH medulloblastoma. Additionally, we performed scRNAseq on 16,000 cells from genetically engineered mouse (GEM) models of GP3 and SHH medulloblastoma. These models showed a level of fidelity with corresponding human subgroup-specific neoplastic and immune subpopulations. Collectively, our findings advance our understanding of the neoplastic and immune landscape of the main medulloblastoma subgroups in both humans and GEM models.

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