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      An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples

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          Abstract

          Establishing clinically relevant single-cell (SC) transcriptomic workflows from cryopreserved tissue is essential to move this emerging immune monitoring technology from the bench to the bedside. Improper sample preparation leads to detrimental cascades, resulting in loss of precious time, money and finally compromised data. There is an urgent need to establish protocols specifically designed to overcome the inevitable variations in sample quality resulting from uncontrollable factors in a clinical setting. Here, we explore sample preparation techniques relevant to a range of clinically relevant scenarios, where SC gene expression and repertoire analysis are applied to a cryopreserved sample derived from a small amount of blood, with unknown or partially known preservation history. We compare a total of ten cell-counting, viability-improvement, and lymphocyte-enrichment methods to highlight a number of unexpected findings. Trypan blue-based automated counters, typically recommended for single-cell sample quantitation, consistently overestimate viability. Advanced sample clean-up procedures significantly impact total cell yield, while only modestly increasing viability. Finally, while pre-enrichment of B cells from whole peripheral blood mononuclear cells (PBMCs) results in the most reliable BCR repertoire data, comparable T-cell enrichment strategies distort the ratio of CD4+ and CD8+ cells. Furthermore, we provide high-resolution analysis of gene expression and clonotype repertoire of different B cell subtypes. Together these observations provide both qualitative and quantitative sample preparation guidelines that increase the chances of obtaining high-quality single-cell transcriptomic and repertoire data from human PBMCs in a variety of clinical settings.

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          Most cited references15

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          A cellular census of human lungs identifies novel cell states in health and in asthma

          Human lungs enable efficient gas exchange and form an interface with the environment, which depends on mucosal immunity for protection against infectious agents. Tightly controlled interactions between structural and immune cells are required to maintain lung homeostasis. Here, we use single-cell transcriptomics to chart the cellular landscape of upper and lower airways and lung parenchyma in healthy lungs, and lower airways in asthmatic lungs. We report location-dependent airway epithelial cell states and a novel subset of tissue-resident memory T cells. In the lower airways of patients with asthma, mucous cell hyperplasia is shown to stem from a novel mucous ciliated cell state, as well as goblet cell hyperplasia. We report the presence of pathogenic effector type 2 helper T cells (TH2) in asthmatic lungs and find evidence for type 2 cytokines in maintaining the altered epithelial cell states. Unbiased analysis of cell-cell interactions identifies a shift from airway structural cell communication in healthy lungs to a TH2-dominated interactome in asthmatic lungs.
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            SPRING: a kinetic interface for visualizing high dimensional single-cell expression data

            Abstract Motivation Single-cell gene expression profiling technologies can map the cell states in a tissue or organism. As these technologies become more common, there is a need for computational tools to explore the data they produce. In particular, visualizing continuous gene expression topologies can be improved, since current tools tend to fragment gene expression continua or capture only limited features of complex population topologies. Results Force-directed layouts of k-nearest-neighbor graphs can visualize continuous gene expression topologies in a manner that preserves high-dimensional relationships and captures complex population topologies. We describe SPRING, a pipeline for data filtering, normalization and visualization using force-directed layouts and show that it reveals more detailed biological relationships than existing approaches when applied to branching gene expression trajectories from hematopoietic progenitor cells and cells of the upper airway epithelium. Visualizations from SPRING are also more reproducible than those of stochastic visualization methods such as tSNE, a state-of-the-art tool. We provide SPRING as an interactive web-tool with an easy to use GUI. Availability and implementation https://kleintools.hms.harvard.edu/tools/spring.html, https://github.com/AllonKleinLab/SPRING/. Supplementary information Supplementary data are available at Bioinformatics online.
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              Fundamentals and application of magnetic particles in cell isolation and enrichment: a review.

              Magnetic sorting using magnetic beads has become a routine methodology for the separation of key cell populations from biological suspensions. Due to the inherent ability of magnets to provide forces at a distance, magnetic cell manipulation is now a standardized process step in numerous processes in tissue engineering, medicine, and in fundamental biological research. Herein we review the current status of magnetic particles to enable isolation and separation of cells, with a strong focus on the fundamental governing physical phenomena, properties and syntheses of magnetic particles and on current applications of magnet-based cell separation in laboratory and clinical settings. We highlight the contribution of cell separation to biomedical research and medicine and detail modern cell-separation methods (both magnetic and non-magnetic). In addition to a review of the current state-of-the-art in magnet-based cell sorting, we discuss current challenges and available opportunities for further research, development and commercialization of magnetic particle-based cell-separation systems.
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                Author and article information

                Contributors
                virginia.savova@sanofi.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 February 2020
                10 February 2020
                2020
                : 10
                : 2219
                Affiliations
                [1 ]Sanofi Immunology and Inflammation Research Therapeutic Area, 270 Albany St, Cambridge, MA 02139 England
                [2 ]ISNI 0000 0004 1936 8753, GRID grid.137628.9, New York University College of Arts and Sciences, ; 32 Waverly Pl, New York, NY 10003 USA
                Article
                58939
                10.1038/s41598-020-58939-y
                7010687
                32042039
                16917383-d976-409e-8d19-7d2a9e043f37
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 November 2019
                : 17 January 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004339, Sanofi;
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                cytological techniques,gene expression analysis,immunological techniques,isolation, separation and purification,sequencing,medical research

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