scholarly journals A targeted multi-omic analysis approach measures protein expression and low abundance transcripts on the single cell level

2019 ◽  
Author(s):  
Florian Mair ◽  
Jami R. Erickson ◽  
Valentin Voillet ◽  
Yannick Simoni ◽  
Timothy Bi ◽  
...  
Keyword(s):  
Protein Expression ◽  
Single Cell ◽  
Cell Function ◽  
Immune Cell ◽  
High Sensitivity ◽  
Read Depth ◽  
Single Cell Level ◽  
Cell Level ◽  
Protein Datasets ◽  
Relationship Of

SummaryHigh throughput single-cell RNA sequencing (sc-RNAseq) has become a frequently used tool to assess immune cell function and heterogeneity. Recently, the combined measurement of RNA and protein expression by sequencing was developed, which is commonly known as CITE-Seq. Acquisition of protein expression data along with transcriptome data resolves some of the limitations inherent to only assessing transcript, but also nearly doubles the sequencing read depth required per single cell. Furthermore, there is still a paucity of analysis tools to visualize combined transcript-protein datasets.Here, we describe a novel targeted transcriptomics approach that combines analysis of over 400 genes with simultaneous measurement of over 40 proteins on more than 25,000 cells. This targeted approach requires only about 1/10 of the read depth compared to a whole transcriptome approach while retaining high sensitivity for low abundance transcripts. To analyze these multi-omic transcript-protein datasets, we adapted One-SENSE for intuitive visualization of the relationship of proteins and transcripts on a single-cell level.

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.

Photothermal Control of Heat-Shock Protein Expression at the Single Cell Level

Small ◽  
2018 ◽  
Vol 14 (32) ◽  
pp. 1801910 ◽  
Author(s):  
Hadrien M. L. Robert ◽  
Julien Savatier ◽  
Stéphanie Vial ◽  
Jacob Verghese ◽  
Benoit Wattellier ◽  
...  
Keyword(s):  
Heat Shock ◽  
Heat Shock Protein ◽  
Protein Expression ◽  
Single Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Heat Shock Protein Expression

scholarly journals A Targeted Multi-omic Analysis Approach Measures Protein Expression and Low-Abundance Transcripts on the Single-Cell Level

Cell Reports ◽  
2020 ◽  
Vol 31 (1) ◽  
pp. 107499 ◽  
Author(s):  
Florian Mair ◽  
Jami R. Erickson ◽  
Valentin Voillet ◽  
Yannick Simoni ◽  
Timothy Bi ◽  
...  
Keyword(s):  
Protein Expression ◽  
Single Cell ◽  
Analysis Approach ◽  
Single Cell Level ◽  
Cell Level

scholarly journals Protein Expression Analyses at the Single Cell Level

Molecules ◽  
2014 ◽  
Vol 19 (9) ◽  
pp. 13932-13947 ◽  
Author(s):  
Masae Ohno ◽  
Peter Karagiannis ◽  
Yuichi Taniguchi
Keyword(s):  
Protein Expression ◽  
Single Cell ◽  
Single Cell Level ◽  
Cell Level

Detection and Quantification of Bacterial Autofluorescence at the Single-Cell Level by a Laboratory-Built High-Sensitivity Flow Cytometer

2012 ◽  
Vol 84 (3) ◽  
pp. 1526-1532 ◽  
Author(s):  
Lingling Yang ◽  
Yingxing Zhou ◽  
Shaobin Zhu ◽  
Tianxun Huang ◽  
Lina Wu ◽  
...  
Keyword(s):  
Single Cell ◽  
High Sensitivity ◽  
Flow Cytometer ◽  
Single Cell Level ◽  
Cell Level ◽  
Detection And Quantification

scholarly journals Visualizing and isolating iron-reducing microorganisms at single cell level

2020 ◽  
Author(s):  
Cuifen Gan ◽  
Rongrong Wu ◽  
Yeshen Luo ◽  
Jianhua Song ◽  
Dizhou Luo ◽  
...  
Keyword(s):  
Single Cell ◽  
Iron Reduction ◽  
High Sensitivity ◽  
Ex Situ ◽  
Single Cell Level ◽  
Cell Level ◽  
Cell Sorter ◽  
Fluorescent Intensity

AbstractIron-reducing microorganisms (FeRM) play key roles in many natural and engineering processes. Visualizing and isolating FeRM from multispecies samples are essential to understand the in-situ location and geochemical role of FeRM. Here, we visualized FeRM by a “turn-on” Fe2+-specific fluorescent chemodosimeter (FSFC) with high sensitivity, selectivity and stability. This FSFC could selectively identify and locate active FeRM from either pure culture, co-culture of different bacteria or sediment-containing samples. Fluorescent intensity of the FSFC could be used as an indicator of Fe2+ concentration in bacterial cultures. By integrating FSFC with a single cell sorter, we obtained three FSFC-labeled cells from an enriched consortia and all of them were subsequently evidenced to be capable of iron-reduction and two unlabeled cells were evidenced to have no iron-reducing capability, further confirming the feasibility of the FSFC.ImportanceVisualization and isolation of FeRM from samples containing multispecies are commonly needed by researchers from different disciplines, such as environmental microbiology, environmental sciences and geochemistry. However, no available method has been reported. In this study, we provid a solution to visualize FeRM and evaluate their activity even at single cell level. Integrating with single cell sorter, FeRM can also be isolated from samples containing multispecies. This method can be used as a powerful tool to uncover the in-situ or ex-situ role of FeRM and their interactions with ambient microbes or chemicals.

scholarly journals Single-cell RNA-Seq reveals the link between CD45 isoforms and tumor-infiltrating T cells heterogeneity in liver cancer

2020 ◽  
Author(s):  
Biaofeng Zhou ◽  
Shang Liu ◽  
Liang Wu ◽  
Yan Sun ◽  
Jie Chen ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Lymphocytes ◽  
Single Cell ◽  
Cell Function ◽  
Effector Memory ◽  
Single Cell Level ◽  
Cell Level ◽  
Cd45 Isoforms ◽  
And Function

AbstractCD45 isoforms play a major role in characterizing T cell function, phenotype, and development. However, there is lacking comprehensive interrogation about the relationship between CD45 isoforms and T lymphocytes from cancer patients at the single-cell level yet. Here, we investigated the CD45 isoforms component of published 5,063 T cells of hepatocellular carcinoma (HCC), which has been assigned functional states. We found that the distribution of CD45 isoforms in T lymphocytes cells depended on tissue resource, cell type, and functional state. Further, we demonstrated that CD45RO and CD45RA dominate in characterizing the phenotype and function of T cell though multiple CD45 isoforms coexist in T cells, through a novel alternative splicing pattern analysis. We identified a novel development trajectory of tumor-infiltrating T cells from Tcm to Temra (effector memory T cells re-expresses CD45RA) after detecting two subpopulations in state of transition, Tcm (central memory T) and Tem (effector memory T). Temra, capable of high cytotoxic characteristics, was discovered to be associated with the stage of HCC and may be a target of immunotherapy. Our study presents a comprehension of the connection between CD45 isoforms and the function, states, sources of T lymphocytes cells in HCC patients at the single-cell level, providing novel insight for the effect of CD45 isoforms on T cell heterogeneity.

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