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Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis

Significant transcriptional heterogeneity is an inherent property of complex tissues such as tumors and healing wounds. Traditional methods of high-throughput analysis rely on pooling gene expression data from hundreds of thousands of cells and reporting a population-wide average that is unable to c...

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Autores principales: Januszyk, Michael, Rennert, Robert C., Sorkin, Michael, Maan, Zeshaan N., Wong, Lisa K., Whittam, Alexander J., Whitmore, Arnetha, Duscher, Dominik, Gurtner, Geoffrey C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996408/
https://www.ncbi.nlm.nih.gov/pubmed/27600239
http://dx.doi.org/10.3390/microarrays4040540
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author Januszyk, Michael
Rennert, Robert C.
Sorkin, Michael
Maan, Zeshaan N.
Wong, Lisa K.
Whittam, Alexander J.
Whitmore, Arnetha
Duscher, Dominik
Gurtner, Geoffrey C.
author_facet Januszyk, Michael
Rennert, Robert C.
Sorkin, Michael
Maan, Zeshaan N.
Wong, Lisa K.
Whittam, Alexander J.
Whitmore, Arnetha
Duscher, Dominik
Gurtner, Geoffrey C.
author_sort Januszyk, Michael
collection PubMed
description Significant transcriptional heterogeneity is an inherent property of complex tissues such as tumors and healing wounds. Traditional methods of high-throughput analysis rely on pooling gene expression data from hundreds of thousands of cells and reporting a population-wide average that is unable to capture differences within distinct cell subsets. Recent advances in microfluidic technology have permitted the development of large-scale single cell analytic methods that overcome this limitation. The increased granularity afforded by such approaches allows us to answer the critical question of whether expansion in cell culture significantly alters the transcriptional characteristics of cells isolated from primary tissue. Here we examine an established population of human adipose-derived stem cells (ASCs) using a novel, microfluidic-based method for high-throughput transcriptional interrogation, coupled with advanced bioinformatic analysis, to evaluate the dynamics of single cell gene expression among primary, passage 0, and passage 1 stem cells. We find significant differences in the transcriptional profiles of cells from each group, as well as a considerable shift in subpopulation dynamics as those subgroups better able to adhere and proliferate under these culture conditions gradually emerge as dominant. Taken together, these findings reinforce the importance of using primary or very early passage cells in future studies.
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spelling pubmed-49964082016-09-06 Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis Januszyk, Michael Rennert, Robert C. Sorkin, Michael Maan, Zeshaan N. Wong, Lisa K. Whittam, Alexander J. Whitmore, Arnetha Duscher, Dominik Gurtner, Geoffrey C. Microarrays (Basel) Article Significant transcriptional heterogeneity is an inherent property of complex tissues such as tumors and healing wounds. Traditional methods of high-throughput analysis rely on pooling gene expression data from hundreds of thousands of cells and reporting a population-wide average that is unable to capture differences within distinct cell subsets. Recent advances in microfluidic technology have permitted the development of large-scale single cell analytic methods that overcome this limitation. The increased granularity afforded by such approaches allows us to answer the critical question of whether expansion in cell culture significantly alters the transcriptional characteristics of cells isolated from primary tissue. Here we examine an established population of human adipose-derived stem cells (ASCs) using a novel, microfluidic-based method for high-throughput transcriptional interrogation, coupled with advanced bioinformatic analysis, to evaluate the dynamics of single cell gene expression among primary, passage 0, and passage 1 stem cells. We find significant differences in the transcriptional profiles of cells from each group, as well as a considerable shift in subpopulation dynamics as those subgroups better able to adhere and proliferate under these culture conditions gradually emerge as dominant. Taken together, these findings reinforce the importance of using primary or very early passage cells in future studies. MDPI 2015-11-04 /pmc/articles/PMC4996408/ /pubmed/27600239 http://dx.doi.org/10.3390/microarrays4040540 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Januszyk, Michael
Rennert, Robert C.
Sorkin, Michael
Maan, Zeshaan N.
Wong, Lisa K.
Whittam, Alexander J.
Whitmore, Arnetha
Duscher, Dominik
Gurtner, Geoffrey C.
Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis
title Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis
title_full Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis
title_fullStr Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis
title_full_unstemmed Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis
title_short Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis
title_sort evaluating the effect of cell culture on gene expression in primary tissue samples using microfluidic-based single cell transcriptional analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996408/
https://www.ncbi.nlm.nih.gov/pubmed/27600239
http://dx.doi.org/10.3390/microarrays4040540
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