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Nat Methods. 2015 Sep;12(9):885-92. doi: 10.1038/nmeth.3507. Epub 2015 Aug 3.

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

Author information

1
The New York Stem Cell Foundation Research Institute, New York, New York, USA.
2
The Broad Institute, Cambridge, Massachusetts, USA.
3
The Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA.
4
Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA.
5
Section on Human Biochemical Genetics, Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.
6
Division of Medical Genomics, Inova Translational Medicine Institute, Inova Health System, Falls Church, Virginia, USA.
7
NIH Undiagnosed Diseases Program, Common Fund, Office of the Director, National Institute of Health and National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, USA.
8
The Howard Hughes Medical Institute, Cambridge, Massachusetts, USA.

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.

PMID:
26237226
DOI:
10.1038/nmeth.3507
[Indexed for MEDLINE]

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