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

Daniel Paull, Ana Sevilla, Hongyan Zhou, Aana Kim Hahn, Hesed Kim, Christopher Napolitano, Alexander Tsankov, Linshan Shang, Katie Krumholz, Premlatha Jagadeesan, Chris M. Woodard, Bruce Sun, Thierry Vilboux, Matthew Zimmer, Eliana Forero, Dorota N. Moroziewicz, Hector Martinez, May Christine V. Malicdan, Keren A. Weiss, Lauren B. VensandCarmen R. Dusenberry, Hannah Polus, Karla Therese L. Sy, David J. Kahler, William A. Gahl, Susan L. Solomon, Stephen Chang, Alexander Meissner, Kevin Eggan, Scott A. Noggle

Research output: Contribution to journalArticle

109 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)885-892
Number of pages8
JournalNature Methods
Volume12
Issue number9
DOIs
StatePublished - Aug 28 2015
Externally publishedYes

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    Paull, D., Sevilla, A., Zhou, H., Hahn, A. K., Kim, H., Napolitano, C., Tsankov, A., Shang, L., Krumholz, K., Jagadeesan, P., Woodard, C. M., Sun, B., Vilboux, T., Zimmer, M., Forero, E., Moroziewicz, D. N., Martinez, H., Malicdan, M. C. V., Weiss, K. A., ... Noggle, S. A. (2015). Automated, high-throughput derivation, characterization and differentiation of induced pluripotent stem cells. Nature Methods, 12(9), 885-892. https://doi.org/10.1038/nmeth.3507