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An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010687/ https://www.ncbi.nlm.nih.gov/pubmed/32042039 http://dx.doi.org/10.1038/s41598-020-58939-y |
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author | Hanamsagar, Richa Reizis, Timothy Chamberlain, Mathew Marcus, Robert Nestle, Frank O. de Rinaldis, Emanuele Savova, Virginia |
author_facet | Hanamsagar, Richa Reizis, Timothy Chamberlain, Mathew Marcus, Robert Nestle, Frank O. de Rinaldis, Emanuele Savova, Virginia |
author_sort | Hanamsagar, Richa |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7010687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70106872020-02-21 An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples Hanamsagar, Richa Reizis, Timothy Chamberlain, Mathew Marcus, Robert Nestle, Frank O. de Rinaldis, Emanuele Savova, Virginia Sci Rep Article 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. Nature Publishing Group UK 2020-02-10 /pmc/articles/PMC7010687/ /pubmed/32042039 http://dx.doi.org/10.1038/s41598-020-58939-y Text en © 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/. |
spellingShingle | Article Hanamsagar, Richa Reizis, Timothy Chamberlain, Mathew Marcus, Robert Nestle, Frank O. de Rinaldis, Emanuele Savova, Virginia An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples |
title | An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples |
title_full | An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples |
title_fullStr | An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples |
title_full_unstemmed | An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples |
title_short | An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples |
title_sort | optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010687/ https://www.ncbi.nlm.nih.gov/pubmed/32042039 http://dx.doi.org/10.1038/s41598-020-58939-y |
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