scholarly journals Advances in single cell technologies in immunology

BioTechniques ◽  
2020 ◽  
Vol 69 (3) ◽  
pp. 226-236
Author(s):  
Jane Ru Choi
Keyword(s):  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Single Cell Level ◽  
Future Perspectives ◽  
Biological Mechanisms ◽  
Cell Level ◽  
Cell Responses ◽  
Physiological Processes ◽  
Cell Technologies

The immune system is composed of heterogeneous populations of immune cells that regulate physiological processes and protect organisms against diseases. Single cell technologies have been used to assess immune cell responses at the single cell level, which are crucial for identifying the causes of diseases and elucidating underlying biological mechanisms to facilitate medical therapy. In the present review we first discuss the most recent advances in the development of single cell technologies to investigate cell signaling, cell–cell interactions and cell migration. Each technology's advantages and limitations and its applications in immunology are subsequently reviewed. The latest progress toward commercialization, the remaining challenges and future perspectives for single cell technologies in immunology are also briefly discussed.

scholarly journals Advanced Genomics-Based Approaches for Defining Allograft Rejection With Single Cell Resolution

2021 ◽  
Vol 12 ◽  
Author(s):  
Tiffany Shi ◽  
Krishna Roskin ◽  
Brian M. Baker ◽  
E. Steve Woodle ◽  
David Hildeman
Keyword(s):  
Single Cell ◽  
Allograft Rejection ◽  
Immune Cell ◽  
Transplant Rejection ◽  
Solid Organ Transplantation ◽  
Genomic Analysis ◽  
Solid Organ ◽  
Single Cell Level ◽  
Cell Level ◽  
Network Analyses

Solid organ transplant recipients require long-term immunosuppression for prevention of rejection. Calcineurin inhibitor (CNI)-based immunosuppressive regimens have remained the primary means for immunosuppression for four decades now, yet little is known about their effects on graft resident and infiltrating immune cell populations. Similarly, the understanding of rejection biology under specific types of immunosuppression remains to be defined. Furthermore, development of innovative, rationally designed targeted therapeutics for mitigating or preventing rejection requires a fundamental understanding of the immunobiology that underlies the rejection process. The established use of microarray technologies in transplantation has provided great insight into gene transcripts associated with allograft rejection but does not characterize rejection on a single cell level. Therefore, the development of novel genomics tools, such as single cell sequencing techniques, combined with powerful bioinformatics approaches, has enabled characterization of immune processes at the single cell level. This can provide profound insights into the rejection process, including identification of resident and infiltrating cell transcriptomes, cell-cell interactions, and T cell receptor α/β repertoires. In this review, we discuss genomic analysis techniques, including microarray, bulk RNAseq (bulkSeq), single-cell RNAseq (scRNAseq), and spatial transcriptomic (ST) techniques, including considerations of their benefits and limitations. Further, other techniques, such as chromatin analysis via assay for transposase-accessible chromatin sequencing (ATACseq), bioinformatic regulatory network analyses, and protein-based approaches are also examined. Application of these tools will play a crucial role in redefining transplant rejection with single cell resolution and likely aid in the development of future immunomodulatory therapies in solid organ transplantation.

Experimental and computational technologies to dissect the kidney at the single-cell level

2020 ◽  
Author(s):  
Christoph Kuppe ◽  
Javier Perales-Patón ◽  
Julio Saez-Rodriguez ◽  
Rafael Kramann
Keyword(s):  
Single Cell ◽  
Computational Methods ◽  
Therapeutic Targets ◽  
Single Cell Level ◽  
Cell Level ◽  
Single Cell Genomics ◽  
Cell Technologies ◽  
Novel Therapeutic

Abstract The field of single-cell technologies, in particular single-cell genomics with transcriptomics and epigenomics, and most recently single-cell proteomics, is rapidly growing and holds promise to advance our understanding of organ homoeostasis and disease, and facilitate the identification of novel therapeutic targets and biomarkers. This review offers an introduction to these technologies. In addition, as the size and complexity of the data require sophisticated computational methods for analysis and interpretation, we will also provide an overview of these methods and summarize the single-cell literature specifically pertaining to the kidney.

scholarly journals Toward an understanding of immune cell sociology: real-time monitoring of cytokine secretion at the single-cell level

IUBMB Life ◽  
2012 ◽  
Vol 65 (1) ◽  
pp. 28-34 ◽  
Author(s):  
Yoshitaka Shirasaki ◽  
Mai Yamagishi ◽  
Nanako Shimura ◽  
Atsushi Hijikata ◽  
Osamu Ohara
Keyword(s):  
Single Cell ◽  
Real Time ◽  
Immune Cell ◽  
Cytokine Secretion ◽  
Single Cell Level ◽  
Real Time Monitoring ◽  
Cell Level

scholarly journals LINE-1 Retrotransposon expression in cancerous, epithelial and neuronal cells revealed by 5’-single cell RNA-Seq

2021 ◽  
Author(s):  
Wilson McKerrow ◽  
Shane A. Evans ◽  
Azucena Rocha ◽  
John Sedivy ◽  
Nicola Neretti ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Early Development ◽  
Immune Cells ◽  
Copy Number ◽  
Single Cells ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Mouse Hippocampus

AbstractLINE-1 retrotransposons are known to be expressed in early development, in tumors and in the germline. Less is known about LINE-1 expression at the single cell level, especially outside the context of cancer. Because LINE-1 elements are present at a high copy number, many transcripts that are not driven by the LINE-1 promoter nevertheless terminate at the LINE-1 3’ UTR. Thus, 3’ targeted single cell RNA-seq datasets are not appropriate for studying LINE-1. However, 5’ targeted single cell datasets provide an opportunity to analyze LINE-1 expression at the single cell level. Most LINE-1 copies are 5’ truncated, and a transcript that contains the LINE-1 5’ UTR as its 5’ end is likely to have been transcribed from its promoter. We developed a method, L1-sc (LINE-1 expression for single cells), to quantify LINE-1 expression in 5’ targeted 10x genomics single cell RNA-seq datasets. Our method confirms that LINE-1 expression is high in cancer cells, but low or absent from immune cells. We also find that LINE-1 expression is elevated in epithelial compared to immune cells outside of the context of cancer and that it is also elevated in neurons compared to glia in the mouse hippocampus.

scholarly journals Mass Cytometry Study on the Heterogeneity in Cellular Association and Cytotoxicity of Silver Nanoparticles in Human Immune Cells

2019 ◽  
Author(s):  
My Kieu Ha ◽  
Jang-Sik Choi ◽  
Zayakhuu Gerelkhuu ◽  
Sook Jin Kwon ◽  
Jaewoo Song ◽  
...  
Keyword(s):  
Silver Nanoparticles ◽  
Adverse Effects ◽  
Single Cell ◽  
Dose Response ◽  
Immune Cells ◽  
Intracellular Signaling ◽  
Single Cell Level ◽  
Mass Cytometry ◽  
Cell Level ◽  
Human Immune

AbstractThere have been many reports about the adverse effects of nanoparticles (NPs) on the environment and human health. Conventional toxicity assessments of NPs frequently assume uniform distribution of monodisperse NPs in homogeneous cell populations, and provide information on the relationships between the administered dose of NPs and cellular responses averaged for a large number of cells. They may have limitations in describing the wide heterogeneity of cell-NP interactions, caused by cell-to-cell and NP-to-NP variances. To achieve more detailed insight into the heterogeneity of cell-NP interactions, it is essential to understand the cellular association and adverse effects of NPs at single-cell level. In this study, we applied mass cytometry to investigate the interactions between silver nanoparticles (AgNPs) and primary human immune cells. High dimensionality of mass cytometry allowed us to identify various immune cell types and observe the cellular association and toxicity of AgNPs in each population. Our findings showed that AgNPs had higher affinity with phagocytic cells like monocytes and dendritic cells and caused more severe toxic effects than with T cells, B cells and NK cells. Multi-element detection capability of mass cytometry also enabled us to simultaneously monitor cellular AgNP dose and intracellular signaling of individual cells, and subsequently investigate the dose-response relationships of each immune population at single-cell level, which are often hidden in conventional toxicity assays at bulk-cell level. Our study will assist future development of single-cell dose-response models for various NPs and will provide key information for the safe use of nanomaterials for biomedical applications.

Abstract 439: High Dimensional Single-Cell Immune Contexture of Human Atherosclerotic Plaques and Blood

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Adeeb Rahman ◽  
Aleksey Chudnovskiy ◽  
El-ad David Amir ◽  
Seunghee Kim-Schulze ◽  
Jennifer R Li ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
High Dimensional ◽  
Specific Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Immune Contexture

Atherosclerosis is a disease characterized by immune infiltration of the arterial wall in response to tissue damage and systemic inflammation. In the era of precision medicine, is essential to gain insights on immune contexture of atherosclerotic tissue taking into account disease-specific cell variation in patients. We applied high-dimensional technologies for the analysis of multiple parameters at the single-cell level in clinical samples of patients undergoing carotid endatherectomy (CEA, n=15). Using time-of-flight mass-cytometry (CyTOF), we simultaneously analyzed 32 parameters at the single-cell level in peripheral blood mononuclear cells (PBMCs) and atherosclerotic-tissue associated immune cells of the same patient. Using viSNE, we mapped single-cell heterogeneity into two dimensions to discriminate PBMCs and tissue-associated CD45+ immune cells. Next, we employed Phenograph to cluster cells into phenotypically related populations, which were annotated based on canonical marker expression patterns. We identified several major immune subsets including two subsets of macrophages (CD163 low and CD163 high ), monocytes, dendritic cells (DCs), B and T cells. The most prevalent CD45+ cells identified in atherosclerotic tissue were CD4 + (25.8%) and CD8 + (25.2%) T cells, macrophages (12.8%), monocytes (7.7%) and B (2.1%) cells. Using a regression analysis similar to that employed by CITRUS, we determined that macrophages and a subset of CD8 T cells characterized by low expression of CD127 were selectively enriched in tissue vs. blood. Multiplexed immunohistochemistry confirmed that T cells comprised a major portion of the CD45+ cells in atherosclerotic tissue, even more abundant than macrophages. This study of deep phenotyping across-atherosclerotic tissue and blood demonstrate a significant T cell tissue infiltration of a specific subset of CD8 T cells. This suggests that adaptive T cell immunity plays a critical role in advanced atherosclerosis. The extension of this systems biology analysis pipeline to larger datasets can improve our understanding of the core mechanisms of chronic inflammation in atherosclerosis.

scholarly journals Resolving Tumour Clonal Heterogeneity and Spatial Complexity using Nuclear Tandem Epitope Protein (nTEP) Barcoding

2018 ◽  
Author(s):  
Michael B. Gill ◽  
Simon Koplev ◽  
Anne C. Machel ◽  
Martin L. Miller
Keyword(s):  
Single Cell ◽  
Immune Cells ◽  
Tumour Microenvironment ◽  
Cellular Level ◽  
Single Cell Level ◽  
Cellular Interactions ◽  
Cell Level ◽  
Cell Clones ◽  
Mouse Tumour ◽  
Novel Protein

ABSTRACTTumours are composed of an array of unique cancer cell clones along with many non-tumour cells such as immune cells, fibroblasts and endothelial cells, which make up the complex tumour microenvironment. To better understand the co-evolution of tumour clones and cells of the tumour microenvironment, we require tools to spatially resolve heterotypic cellular interactions at the single cell level. We present a novel protein-based barcoding technology termed nuclear tandem epitope protein (nTEP) barcoding, which can be designed to combinatorially encode and track dozens to hundreds of tumour clones in their spatial context within complex cellular mixtures using multiplexed antibody-based imaging. Here we provide proof-of-principle of nTEP barcoding and develop the technology, which relies on lentiviral - based stable expression of a nuclear-localised fluorophore that contains unique combinations of protein epitope tags that can be decoded by a limited set of antibodies. By generating a series of cell lines expressing unique nTEP barcodes, we were able to robustly identify and spatially deconvolve specific clones present within highly complex cell mixtures at the single cell level using state-of-the-art iterative indirect immunofluorescence imaging (4i). We define the utility of nTEP-barcoding as a powerful tool for visualising and resolving tumour heterogeneity at the cellular level, and envision its usage in mouse tumour models for understanding how tumour clones modulate and interact with stromal- and immune cells in cancer.

scholarly journals A rapid and robust method for single cell chromatin accessibility profiling

2018 ◽  
Author(s):  
Xi Chen ◽  
Ricardo J Miragaia ◽  
Kedar Nath Natarajan ◽  
Sarah A Teichmann
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Single Cell Level ◽  
Cell Type ◽  
Cell Level ◽  
Regulatory Regions ◽  
Cell Type Specific ◽  
Accessible Chromatin

AbstractThe assay for transposase-accessible chromatin using sequencing (ATAC-seq) is widely used to identify regulatory regions throughout the genome. However, very few studies have been performed at the single cell level (scATAC-seq) due to technical challenges. Here we developed a simple and robust plate-based scATAC-seq method, combining upfront bulk Tn5 tagging with single-nuclei sorting. We demonstrated that our method worked robustly across various systems, including fresh and cryopreserved cells from primary tissues. By profiling over 3,000 splenocytes, we identify distinct immune cell types and reveal cell type-specific regulatory regions and related transcription factors.

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