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Automated, high-throughput derivation, characterization and differentiation of induced pluripotent stem cells.

Authors :
Paull, Daniel
Sevilla, Ana
Zhou, Hongyan
Hahn, Aana Kim
Kim, Hesed
Napolitano, Christopher
Tsankov, Alexander
Shang, Linshan
Krumholz, Katie
Jagadeesan, Premlatha
Woodard, Chris M
Sun, Bruce
Vilboux, Thierry
Zimmer, Matthew
Forero, Eliana
Moroziewicz, Dorota N
Martinez, Hector
Malicdan, May Christine V
Weiss, Keren A
Vensand, Lauren B
Source :
Nature Methods; Sep2015, Vol. 12 Issue 9, p885-892, 8p, 4 Color Photographs, 1 Chart, 1 Graph
Publication Year :
2015

Abstract

Induced pluripotent stem cells (iPSCs) are an essential tool for modeling how causal genetic variants impact cellular function in disease, as well as an emerging source of tissue for regenerative medicine. The preparation of somatic cells, their reprogramming and the subsequent verification of iPSC pluripotency are laborious, manual processes limiting the scale and reproducibility of this technology. Here we describe a modular, robotic platform for iPSC reprogramming enabling automated, high-throughput conversion of skin biopsies into iPSCs and differentiated cells with minimal manual intervention. We demonstrate that automated reprogramming and the pooled selection of polyclonal pluripotent cells results in high-quality, stable iPSCs. These lines display less line-to-line variation than either manually produced lines or lines produced through automation followed by single-colony subcloning. The robotic platform we describe will enable the application of iPSCs to population-scale biomedical problems including the study of complex genetic diseases and the development of personalized medicines. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15487091
Volume :
12
Issue :
9
Database :
Complementary Index
Journal :
Nature Methods
Publication Type :
Academic Journal
Accession number :
109166043
Full Text :
https://doi.org/10.1038/nmeth.3507