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Efficient Feeder-Free Episomal Reprogramming with Small Molecules

Overview of attention for article published in PLOS ONE, March 2011
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Title
Efficient Feeder-Free Episomal Reprogramming with Small Molecules
Published in
PLOS ONE, March 2011
DOI 10.1371/journal.pone.0017557
Pubmed ID
Authors

Junying Yu, Kevin Fongching Chau, Maxim A. Vodyanik, Jinlan Jiang, Yong Jiang

Abstract

Genetic reprogramming of human somatic cells to induced pluripotent stem cells (iPSCs) could offer replenishable cell sources for transplantation therapies. To fulfill their promises, human iPSCs will ideally be free of exogenous DNA (footprint-free), and be derived and cultured in chemically defined media free of feeder cells. Currently, methods are available to enable efficient derivation of footprint-free human iPSCs. However, each of these methods has its limitations. We have previously derived footprint-free human iPSCs by employing episomal vectors for transgene delivery, but the process was inefficient and required feeder cells. Here, we have greatly improved the episomal reprogramming efficiency using a cocktail containing MEK inhibitor PD0325901, GSK3β inhibitor CHIR99021, TGF-β/Activin/Nodal receptor inhibitor A-83-01, ROCK inhibitor HA-100 and human leukemia inhibitory factor. Moreover, we have successfully established a feeder-free reprogramming condition using chemically defined medium with bFGF and N2B27 supplements and chemically defined human ESC medium mTeSR1 for the derivation of footprint-free human iPSCs. These improvements enabled the routine derivation of footprint-free human iPSCs from skin fibroblasts, adipose tissue-derived cells and cord blood cells. This technology will likely be valuable for the production of clinical-grade human iPSCs.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 309 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 2%
Brazil 5 2%
Germany 2 <1%
Switzerland 1 <1%
United Kingdom 1 <1%
France 1 <1%
China 1 <1%
Mexico 1 <1%
Unknown 291 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 78 25%
Researcher 65 21%
Student > Bachelor 31 10%
Student > Master 29 9%
Professor 19 6%
Other 56 18%
Unknown 31 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 147 48%
Biochemistry, Genetics and Molecular Biology 49 16%
Medicine and Dentistry 36 12%
Neuroscience 14 5%
Engineering 9 3%
Other 16 5%
Unknown 38 12%