論文

査読有り
2015年6月

Efficient Detection and Purification of Cell Populations Using Synthetic MicroRNA Switches

CELL STEM CELL
  • Kenji Miki
  • Kei Endo
  • Seiya Takahashi
  • Shunsuke Funakoshi
  • Ikue Takei
  • Shota Katayama
  • Taro Toyoda
  • Maki Kotaka
  • Tadashi Takaki
  • Masayuki Umeda
  • Chikako Okubo
  • Misato Nishikawa
  • Akiko Oishi
  • Megumi Narita
  • Ito Miyashita
  • Kanako Asano
  • Karin Hayashi
  • Kenji Osafune
  • Shinya Yamanaka
  • Hirohide Saito
  • Yoshinori Yoshida
  • 全て表示

16
6
開始ページ
699
終了ページ
711
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.stem.2015.04.005
出版者・発行元
CELL PRESS

Isolation of specific cell types, including pluripotent stem cell (PSC)-derived populations, is frequently accomplished using cell surface antigens expressed by the cells of interest. However, specific antigens for many cell types have not been identified, making their isolation difficult. Here, we describe an efficient method for purifying cells based on endogenous miRNA activity. We designed synthetic mRNAs encoding a fluorescent protein tagged with sequences targeted by miRNAs expressed by the cells of interest. These miRNA switches control their translation levels by sensing miRNA activities. Several miRNA switches (miR-1-, miR-208a-, and miR-499a-5p-switches) efficiently purified cardiomyocytes differentiated from human PSCs, and switches encoding the apoptosis inducer Bim enriched for cardiomyocytes without cell sorting. This approach is generally applicable, as miR-126-, miR-122-5p-, and miR-375-switches purified endothelial cells, hepatocytes, and insulin-producing cells differentiated from hPSCs, respectively. Thus, miRNA switches can purify cell populations for which other isolation strategies are unavailable.

リンク情報
DOI
https://doi.org/10.1016/j.stem.2015.04.005
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/26004781
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000355932300017&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.stem.2015.04.005
  • ISSN : 1934-5909
  • eISSN : 1875-9777
  • PubMed ID : 26004781
  • Web of Science ID : WOS:000355932300017

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