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Efficient iPS Cell Production with the MyoD Transactivation Domain in Serum-Free Culture

Overview of attention for article published in PLOS ONE, March 2012
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Title
Efficient iPS Cell Production with the MyoD Transactivation Domain in Serum-Free Culture
Published in
PLOS ONE, March 2012
DOI 10.1371/journal.pone.0034149
Pubmed ID
Authors

Hiroyuki Hirai, Nobuko Katoku-Kikyo, Peter Karian, Meri Firpo, Nobuaki Kikyo

Abstract

A major difficulty of producing induced pluripotent stem cells (iPSCs) has been the low efficiency of reprogramming differentiated cells into pluripotent cells. We previously showed that 5% of mouse embryonic fibroblasts (MEFs) were reprogrammed into iPSCs when they were transduced with a fusion gene composed of Oct4 and the transactivation domain of MyoD (called M(3)O), along with Sox2, Klf4 and c-Myc (SKM). In addition, M(3)O facilitated chromatin remodeling of pluripotency genes in the majority of transduced MEFs, including cells that did not become iPSCs. These observations suggested the possibility that more than 5% of cells had acquired the ability to become iPSCs given more favorable culture conditions. Here, we raised the efficiency of making mouse iPSCs with M(3)O-SKM to 26% by culturing transduced cells at low density in serum-free culture medium. In contrast, the efficiency increased from 0.1% to only 2% with the combination of wild-type Oct4 and SKM (OSKM) under the same culture condition. For human iPSCs, M(3)O-SKM achieved 7% efficiency under a similar serum-free culture condition, in comparison to 1% efficiency with OSKM. This study highlights the power of combining the transactivation domain of MyoD with a favorable culture environment.

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Geographical breakdown

Country Count As %
United States 3 5%
Portugal 1 2%
South Africa 1 2%
Unknown 58 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 29%
Student > Ph. D. Student 11 17%
Other 6 10%
Student > Master 6 10%
Professor 4 6%
Other 10 16%
Unknown 8 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 38%
Biochemistry, Genetics and Molecular Biology 17 27%
Medicine and Dentistry 7 11%
Computer Science 2 3%
Engineering 2 3%
Other 2 3%
Unknown 9 14%