Drop-on-demand single cell isolation and total RNA analysis.

Technologies that rapidly isolate viable single cells from heterogeneous solutions have significantly contributed to the field of medical genomics. Challenges remain both to enable efficient extraction, isolation and patterning of single cells from heterogeneous solutions as well as to keep them ali...

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Main Authors: Sangjun Moon, Yun-Gon Kim, Lingsheng Dong, Michael Lombardi, Edward Haeggstrom, Roderick V Jensen, Li-Li Hsiao, Utkan Demirci
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-03-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3055874?pdf=render
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spelling doaj-f0c4d02ea93546f7b709dede8d1046ce2020-11-25T01:21:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-03-0163e1745510.1371/journal.pone.0017455Drop-on-demand single cell isolation and total RNA analysis.Sangjun MoonYun-Gon KimLingsheng DongMichael LombardiEdward HaeggstromRoderick V JensenLi-Li HsiaoUtkan DemirciTechnologies that rapidly isolate viable single cells from heterogeneous solutions have significantly contributed to the field of medical genomics. Challenges remain both to enable efficient extraction, isolation and patterning of single cells from heterogeneous solutions as well as to keep them alive during the process due to a limited degree of control over single cell manipulation. Here, we present a microdroplet based method to isolate and pattern single cells from heterogeneous cell suspensions (10% target cell mixture), preserve viability of the extracted cells (97.0±0.8%), and obtain genomic information from isolated cells compared to the non-patterned controls. The cell encapsulation process is both experimentally and theoretically analyzed. Using the isolated cells, we identified 11 stem cell markers among 1000 genes and compare to the controls. This automated platform enabling high-throughput cell manipulation for subsequent genomic analysis employs fewer handling steps compared to existing methods.http://europepmc.org/articles/PMC3055874?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Sangjun Moon
Yun-Gon Kim
Lingsheng Dong
Michael Lombardi
Edward Haeggstrom
Roderick V Jensen
Li-Li Hsiao
Utkan Demirci
spellingShingle Sangjun Moon
Yun-Gon Kim
Lingsheng Dong
Michael Lombardi
Edward Haeggstrom
Roderick V Jensen
Li-Li Hsiao
Utkan Demirci
Drop-on-demand single cell isolation and total RNA analysis.
PLoS ONE
author_facet Sangjun Moon
Yun-Gon Kim
Lingsheng Dong
Michael Lombardi
Edward Haeggstrom
Roderick V Jensen
Li-Li Hsiao
Utkan Demirci
author_sort Sangjun Moon
title Drop-on-demand single cell isolation and total RNA analysis.
title_short Drop-on-demand single cell isolation and total RNA analysis.
title_full Drop-on-demand single cell isolation and total RNA analysis.
title_fullStr Drop-on-demand single cell isolation and total RNA analysis.
title_full_unstemmed Drop-on-demand single cell isolation and total RNA analysis.
title_sort drop-on-demand single cell isolation and total rna analysis.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2011-03-01
description Technologies that rapidly isolate viable single cells from heterogeneous solutions have significantly contributed to the field of medical genomics. Challenges remain both to enable efficient extraction, isolation and patterning of single cells from heterogeneous solutions as well as to keep them alive during the process due to a limited degree of control over single cell manipulation. Here, we present a microdroplet based method to isolate and pattern single cells from heterogeneous cell suspensions (10% target cell mixture), preserve viability of the extracted cells (97.0±0.8%), and obtain genomic information from isolated cells compared to the non-patterned controls. The cell encapsulation process is both experimentally and theoretically analyzed. Using the isolated cells, we identified 11 stem cell markers among 1000 genes and compare to the controls. This automated platform enabling high-throughput cell manipulation for subsequent genomic analysis employs fewer handling steps compared to existing methods.
url http://europepmc.org/articles/PMC3055874?pdf=render
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