Single-cell RNA sequencing reveals the heterogeneity of infiltrating immune cell profiles in the hepatic cystic echinococcosis microenvironment

Human cystic echinococcosis, caused by the larval stage of echinococcus granulus sensu lato , has been reported a near-cosmopolitan zoonotic disease. Various infiltrating immune cells gather around the lesion and produce lesion microenvironment, however cellular composition and heterogeneity in hepatic cystic echinococcosis lesion microenvironment are incompletely understood. Here, 81,865 immune cells isolated from peripheral blood, peri-lesion liver tissue, and adjacent normal liver tissue from four cystic echinococcosis patients were profiled using single-cell RNA sequencing. We identified 23 discrete cell populations, and found distinct differences in infiltrating immune cells between tissue environments. Despite the significant similarity between peri-lesion and adjacent normal liver tissue-resident immune cells, the cellular proportions of innate lymphocyte 2 and plasmacytoid dendritic cells were higher in peri-lesion liver tissue. Interestingly, the immunosuppressive gene NFKBIA was up-regulated in these cells. Seven subsets of CD4 + T cell populations were found, and there were more Treg-CD4 + T and Th2-CD4 + T cells in peri-lesion tissue than those in adjacent normal tissue. There was close contact between CD4 + T cells and ILC2 and pDCs cells, which caused up-regulation of genes related to positive immune activity in adjacent normal liver tissue. However, expression of genes related to immunosuppression, especially the immune inhibitory checkpoint gene NKG2A/HLA-E, was obviously higher in peri-lesion tissue, suggesting that cellular interaction resulted in an inhibitory microenvironment in the CE lesion. This work offers new insights into the transcriptional heterogeneity of infiltrating immune cells in hepatic cystic echinococcosis lesion microenvironment at single-cell level, and provides potential target signatures for diagnosis and immunotherapies.

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Reference Transcriptomes of Porcine Peripheral Immune Cells Created Through Bulk and Single-Cell RNA Sequencing

Frontiers in Genetics ◽

10.3389/fgene.2021.689406 ◽

2021 ◽

Vol 12 ◽

Author(s):

Juber Herrera-Uribe ◽

Jayne E. Wiarda ◽

Sathesh K. Sivasankaran ◽

Lance Daharsh ◽

Haibo Liu ◽

...

Keyword(s):

T Cells ◽

Single Cell ◽

Immune Cells ◽

Peripheral Blood ◽

Cell Types ◽

Cell Populations ◽

Rna Seq ◽

Cell Type ◽

Transcriptomic Data ◽

Single Cell Rna Sequencing

Pigs are a valuable human biomedical model and an important protein source supporting global food security. The transcriptomes of peripheral blood immune cells in pigs were defined at the bulk cell-type and single cell levels. First, eight cell types were isolated in bulk from peripheral blood mononuclear cells (PBMCs) by cell sorting, representing Myeloid, NK cells and specific populations of T and B-cells. Transcriptomes for each bulk population of cells were generated by RNA-seq with 10,974 expressed genes detected. Pairwise comparisons between cell types revealed specific expression, while enrichment analysis identified 1,885 to 3,591 significantly enriched genes across all 8 cell types. Gene Ontology analysis for the top 25% of significantly enriched genes (SEG) showed high enrichment of biological processes related to the nature of each cell type. Comparison of gene expression indicated highly significant correlations between pig cells and corresponding human PBMC bulk RNA-seq data available in Haemopedia. Second, higher resolution of distinct cell populations was obtained by single-cell RNA-sequencing (scRNA-seq) of PBMC. Seven PBMC samples were partitioned and sequenced that produced 28,810 single cell transcriptomes distributed across 36 clusters and classified into 13 general cell types including plasmacytoid dendritic cells (DC), conventional DCs, monocytes, B-cell, conventional CD4 and CD8 αβ T-cells, NK cells, and γδ T-cells. Signature gene sets from the human Haemopedia data were assessed for relative enrichment in genes expressed in pig cells and integration of pig scRNA-seq with a public human scRNA-seq dataset provided further validation for similarity between human and pig data. The sorted porcine bulk RNAseq dataset informed classification of scRNA-seq PBMC populations; specifically, an integration of the datasets showed that the pig bulk RNAseq data helped define the CD4CD8 double-positive T-cell populations in the scRNA-seq data. Overall, the data provides deep and well-validated transcriptomic data from sorted PBMC populations and the first single-cell transcriptomic data for porcine PBMCs. This resource will be invaluable for annotation of pig genes controlling immunogenetic traits as part of the porcine Functional Annotation of Animal Genomes (FAANG) project, as well as further study of, and development of new reagents for, porcine immunology.

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Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma

Oncogene ◽

10.1038/s41388-021-02054-3 ◽

2021 ◽

Author(s):

Philip Bischoff ◽

Alexandra Trinks ◽

Benedikt Obermayer ◽

Jan Patrick Pett ◽

Jennifer Wiederspahn ◽

...

Keyword(s):

T Cells ◽

Dendritic Cells ◽

Tumor Microenvironment ◽

Lung Adenocarcinoma ◽

Single Cell ◽

Rna Sequencing ◽

Histological Grade ◽

Cell Populations ◽

Marker Genes ◽

Single Cell Rna Sequencing

AbstractRecent developments in immuno-oncology demonstrate that not only cancer cells, but also the tumor microenvironment can guide precision medicine. A comprehensive and in-depth characterization of the tumor microenvironment is challenging since its cell populations are diverse and can be important even if scarce. To identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to ten human lung adenocarcinomas and ten normal control tissues. Our analyses revealed heterogeneous carcinoma cell transcriptomes reflecting histological grade and oncogenic pathway activities, and two distinct microenvironmental patterns. The immune-activated CP²E microenvironment was composed of cancer-associated myofibroblasts, proinflammatory monocyte-derived macrophages, plasmacytoid dendritic cells and exhausted CD8+ T cells, and was prognostically unfavorable. In contrast, the inert N³MC microenvironment was characterized by normal-like myofibroblasts, non-inflammatory monocyte-derived macrophages, NK cells, myeloid dendritic cells and conventional T cells, and was associated with a favorable prognosis. Microenvironmental marker genes and signatures identified in single-cell profiles had progonostic value in bulk tumor profiles. In summary, single-cell RNA profiling of lung adenocarcinoma provides additional prognostic information based on the microenvironment, and may help to predict therapy response and to reveal possible target cell populations for future therapeutic approaches.

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Chicken peripheral blood lymphocyte response to ALV-J infection assessed by single-cell RNA sequencing

10.1101/2021.01.12.426350 ◽

2021 ◽

Author(s):

Manman Dai ◽

Min Feng ◽

Ziwei Li ◽

Weisan Chen ◽

Ming Liao

Keyword(s):

T Cells ◽

T Cell ◽

Viral Infection ◽

Single Cell ◽

Rna Sequencing ◽

Peripheral Blood ◽

Cell Populations ◽

Control Group ◽

Marker Genes ◽

Single Cell Rna Sequencing

ABSTRACTChicken peripheral blood lymphocytes (PBLs) exhibit wide-ranging cell types, but current understanding of their subclasses, immune cell classification, and function is limited and incomplete. Previously, we found that viremia caused by avian leukosis virus subgroup J (ALV‐J) was eliminated by 21 days post infection (DPI), accompanied by increased CD8+ T cell ratio in PBLs and low antibody levels. Here we performed single-cell RNA sequencing (scRNA-seq) of PBLs in ALV-J infected and control chickens at 21 DPI to determine chicken PBL subsets and their specific molecular and cellular characteristics, before and after viral infection. Eight cell clusters and their potential marker genes were identified in chicken PBLs. T cell populations (clusters 6 and 7) had the strongest response to ALV-J infection at 21 DPI, based on detection of the largest number of differentially expressed genes (DEGs). T cell populations of clusters 6 and 7 could be further divided into four subsets: activated CD4+ T cells (cluster A0), Th1-like cells (cluster A2), Th2-like cells (cluster A1), and cytotoxic CD8+ T cells. Hallmark genes for each T cell subset response to viral infection were initially identified. Furthermore, pseudotime analysis results suggested that chicken CD4+ T cells could potentially differentiate into Th1-like and Th2-like cells. Moreover, ALV-J infection probably induced CD4+ T cell differentiation into Th1-like cells in which the most immune related DEGs were detected. With respect to the control group, ALV-J infection also had an obvious impact on PBL cell composition. B cells showed inconspicuous response and their numbers decreased in PBLs of the ALV-J infected chickens at 21 DPI. Percentages of cytotoxic Th1-like cells and CD8+ T cells were increased in the T cell population of PBLs from ALV-J infected chicken, which were potentially key mitigating factors against ALV-J infection. More importantly, our results provided a rich resource of gene expression profiles of chicken PBL subsets for a systems-level understanding of their function in homeostatic condition as well as in response to viral infection.

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Atlas of breast cancer infiltrated B-lymphocytes revealed by paired single-cell RNA-sequencing and antigen receptor profiling

Nature Communications ◽

10.1038/s41467-021-22300-2 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Qingtao Hu ◽

Yu Hong ◽

Pan Qi ◽

Guangqing Lu ◽

Xueying Mai ◽

...

Keyword(s):

Breast Cancer ◽

B Cells ◽

B Cell ◽

Single Cell ◽

Rna Sequencing ◽

B Lymphocytes ◽

Immune Cells ◽

Antigen Receptor ◽

Cell Populations ◽

Single Cell Rna Sequencing

AbstractTo gain mechanistic insights into the functions and developmental dynamics of tumor-infiltrated immune cells, especially B-lymphocytes, here we combine single-cell RNA-sequencing and antigen receptor lineage analysis to characterize a large number of triple-negative breast cancer infiltrated immune cells and report a comprehensive atlas of tumor-infiltrated B-lymphocytes. The single-cell transcriptional profiles reveal significant heterogeneity in tumor-infiltrated B-cell subgroups. The single-cell antigen receptor analyses demonstrate that compared with those in peripheral blood, tumor-infiltrated B-cells have more mature and memory B-cell characteristics, higher clonality, more class switching recombination and somatic hypermutations. Combined analyses suggest local differentiation of infiltrated memory B-cells within breast tumors. The B-cell signatures based on the single-cell RNA-sequencing results are significantly associated with improved survival in breast tumor patients. Functional analyses of tumor-infiltrated B-cell populations suggest that mechanistically, B-cell subgroups may contribute to immunosurveillance through various pathways. Further dissection of tumor-infiltrated B-cell populations will provide valuable clues for tumor immunotherapy.

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Single-cell RNA sequencing reveals compartmental remodeling of tumor-infiltrating immune cells induced by anti-CD47 targeting in pancreatic cancer

Journal of Hematology & Oncology ◽

10.1186/s13045-019-0822-6 ◽

2019 ◽

Vol 12 (1) ◽

Cited By ~ 6

Author(s):

Yu Pan ◽

Fengchun Lu ◽

Qinglin Fei ◽

Xingxing Yu ◽

Ping Xiong ◽

...

Keyword(s):

T Cells ◽

Single Cell ◽

Rna Sequencing ◽

Immune Cells ◽

Tumor Burden ◽

Ductal Adenocarcinoma ◽

Syngeneic Mouse Model ◽

Single Cell Rna Sequencing ◽

Tumor Expression ◽

Inflammatory Macrophages

Abstract Background Human pancreatic ductal adenocarcinoma (PDAC) responds poorly to immune checkpoint inhibitor (ICPi). While the mechanism is not completely clear, it has been recognized that tumor microenvironment (TME) plays key roles. We investigated if targeting CD47 with a monoclonal antibody could enhance the response of PDAC to ICPi by altering the TME. Methods Using immunohistochemistry, we examined tumor-infiltrating CD68+ pan-macrophages (CD68+ M) and CD163+ M2 macrophages (CD163+ M2) and tumor expression of CD47 and PD-L1 proteins in 106 cases of PDAC. The efficacy of CD47 blockade was examined in xenograft models. CD45+ immune cells from syngeneic tumor models were subjected to single-cell RNA-sequencing (scRNA-seq) by using the 10x Genomics pipeline. Results We found that CD47 expression correlated with the level of CD68+ M but not CD163+ M2. High levels of tumor-infiltrating CD68+ M, CD163+ M2, and CD47 expression were significantly associated with worse survival. CD47high/CD68+ Mhigh and CD47high/CD163+ M2high correlated significantly with shorter survival, whereas CD47low/CD68+ Mlow and CD47low/CD163+ M2low correlated with longer survival. Intriguingly, CD47 blockade decreased the tumor burden in the Panc02 but not in the MPC-83 syngeneic mouse model. Using scRNA-seq, we showed that anti-CD47 treatment significantly remodeled the intratumoral lymphocyte and macrophage compartments in Panc02 tumor-bearing mice by increasing the pro-inflammatory macrophages that exhibit anti-tumor function, while reducing the anti-inflammatory macrophages. Moreover, CD47 blockade not only increased the number of intratumoral CD8+ T cells, but also remodeled the T cell cluster toward a more activated one. Further, combination therapy targeting both CD47 and PD-L1 resulted in synergistic inhibition of PDAC growth in the MPC-83 but not in Panc02 model. MPC-83 but not Panc02 mice treated with both anti-CD47 and anti-PD-L1 showed increased number of PD-1+CD8+ T cells and enhanced expression of key immune activating genes. Conclusion Our data indicate that CD47 targeting induces compartmental remodeling of tumor-infiltrating immune cells of the TME in PDAC. Different PDAC mouse models exhibited differential response to the anti-CD47 and anti-PD-L1 blockade due to the differential effect of this combination treatment on the infiltrating immune cells and key immune activating genes in the TME established by the different PDAC cell lines.

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Reference transcriptomes of porcine peripheral immune cells created through bulk and single-cell RNA sequencing

10.1101/2021.04.02.438107 ◽

2021 ◽

Author(s):

Juber Herrera-Uribe ◽

Jayne E Wiarda ◽

Sathesh K Sivasankaran ◽

Lance Daharsh ◽

Haibo Liu ◽

...

Keyword(s):

T Cells ◽

Single Cell ◽

Immune Cells ◽

Peripheral Blood ◽

Cell Types ◽

Cell Populations ◽

Rna Seq ◽

Cell Type ◽

Transcriptomic Data ◽

Single Cell Rna Sequencing

Pigs are a valuable human biomedical model and an important protein source supporting global food security. The transcriptomes of peripheral blood immune cells in pigs were defined at the bulk cell-type and single cell levels. First, eight cell types were isolated in bulk from peripheral blood mononuclear cells (PBMCs) by cell sorting, representing Myeloid, NK cells and specific populations of T and B cells. Transcriptomes for each bulk population of cells were generated by RNA-seq with 10,974 expressed genes detected. Pairwise comparisons between cell types revealed specific expression, while enrichment analysis identified 1,885 to 3,591 significantly enriched genes across all 8 cell types. Gene Ontology analysis for the top 25% of significantly enriched genes (SEG) showed high enrichment of biological processes related to the nature of each cell type. Comparison of gene expression indicated highly significant correlations between pig cells and corresponding human PBMC bulk RNA-seq data available in Haemopedia. Second, higher resolution of distinct cell populations was obtained by single-cell RNA-sequencing (scRNA-seq) of PBMC. Seven PBMC samples were partitioned and sequenced that produced 28,810 single cell transcriptomes distributed across 36 clusters and classified into 13 general cell types including plasmacytoid dendritic cells (DC), conventional DCs, monocytes, B cell, conventional CD4 and CD8 αβ T cells, NK cells, and γδ T cells. Signature gene sets from the human Haemopedia data were assessed for relative enrichment in genes expressed in pig cells and integration of pig scRNA-seq with a public human scRNA-seq dataset provided further validation for similarity between human and pig data. The sorted porcine bulk RNAseq dataset informed classification of scRNA-seq PBMC populations; specifically, an integration of the datasets showed that the pig bulk RNAseq data helped define the CD4CD8 double-positive T cell populations in the scRNA-seq data. Overall, the data provides deep and well-validated transcriptomic data from sorted PBMC populations and the first single-cell transcriptomic data for porcine PBMCs. This resource will be invaluable for annotation of pig genes controlling immunogenetic traits as part of the porcine Functional Annotation of Animal Genomes (FAANG) project, as well as further study of, and development of new reagents for, porcine immunology.

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Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through ‘reverse phenotyping’

Nature Communications ◽

10.1038/s41467-021-24730-4 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

David S. Fischer ◽

Meshal Ansari ◽

Karolin I. Wagner ◽

Sebastian Jarosch ◽

Yiqi Huang ◽

...

Keyword(s):

T Cells ◽

Single Cell ◽

Rna Sequencing ◽

Ex Vivo ◽

Severe Disease ◽

Human Leukocyte ◽

Cell Receptor ◽

Single Cell Rna Sequencing

AbstractThe in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for ‘reverse phenotyping’. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.

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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 ◽

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.

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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 ◽

Single Cell Rna Sequencing

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

10.17504/protocols.io.bz4qp8vw ◽

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.

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