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

Michael Januszyk, Robert C Rennert, Michael Sorkin, Zeshaan N Maan, Lisa K Wong, Alexander J Whittam, Arnetha Whitmore, Dominik Duscher, Geoffrey C Gurtner
{"title":"Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis.","authors":"Michael Januszyk,&nbsp;Robert C Rennert,&nbsp;Michael Sorkin,&nbsp;Zeshaan N Maan,&nbsp;Lisa K Wong,&nbsp;Alexander J Whittam,&nbsp;Arnetha Whitmore,&nbsp;Dominik Duscher,&nbsp;Geoffrey C Gurtner","doi":"10.3390/microarrays4040540","DOIUrl":null,"url":null,"abstract":"<p><p>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. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"4 4","pages":"540-50"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays4040540","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microarrays","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/microarrays4040540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37

Abstract

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.

Abstract Image

Abstract Image

Abstract Image

利用微流体单细胞转录分析评估细胞培养对原代组织样本基因表达的影响。
显著的转录异质性是复杂组织如肿瘤和愈合伤口的固有特性。传统的高通量分析方法依赖于汇集来自数十万个细胞的基因表达数据,并报告整个人群的平均值,而无法捕获不同细胞亚群中的差异。微流体技术的最新进展使大规模单细胞分析方法的发展能够克服这一限制。这种方法所提供的增加的粒度使我们能够回答细胞培养中的扩增是否显着改变原代组织中分离的细胞的转录特性的关键问题。在这里,我们使用一种新型的、基于微流体的高通量转录询问方法,结合先进的生物信息学分析,研究了已建立的人类脂肪源性干细胞(ASCs)群体,以评估原代、传代0和传代1干细胞中单细胞基因表达的动态。我们发现每组细胞的转录谱存在显著差异,同时亚群动态也发生了相当大的变化,因为在这些培养条件下,那些能够更好地粘附和增殖的亚群逐渐成为优势。综上所述,这些发现加强了在未来研究中使用原代或非常早期传代细胞的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
审稿时长
11 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信