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. Vensand; Carmen 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

doi:10.1038/nmeth.3507

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 journal › Article › peer-review

188 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 language	English
Pages (from-to)	885-892
Number of pages	8
Journal	Nature Methods
Volume	12
Issue number	9
DOIs	https://doi.org/10.1038/nmeth.3507
State	Published - 28 Aug 2015
Externally published	Yes

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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

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

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.",

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

note = "Publisher Copyright: {\textcopyright} 2015 Nature America, Inc.",

year = "2015",

month = aug,

day = "28",

doi = "10.1038/nmeth.3507",

language = "English",

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Paull, D, Sevilla, A, Zhou, H, Hahn, AK, Kim, H, Napolitano, C, Tsankov, A, Shang, L, Krumholz, K, Jagadeesan, P, Woodard, CM, Sun, B, Vilboux, T, Zimmer, M, Forero, E, Moroziewicz, DN, Martinez, H, Malicdan, MCV, Weiss, KA, Vensand, LB, Dusenberry, CR, Polus, H, Sy, KTL, Kahler, DJ, Gahl, WA, Solomon, SL, Chang, S, Meissner, A, Eggan, K & Noggle, SA 2015, 'Automated, high-throughput derivation, characterization and differentiation of induced pluripotent stem cells', Nature Methods, vol. 12, no. 9, pp. 885-892. https://doi.org/10.1038/nmeth.3507

TY - JOUR

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AU - Paull, Daniel

AU - Sevilla, Ana

AU - Zhou, Hongyan

AU - Hahn, Aana Kim

AU - Kim, Hesed

AU - Napolitano, Christopher

AU - Tsankov, Alexander

AU - Shang, Linshan

AU - Krumholz, Katie

AU - Jagadeesan, Premlatha

AU - Woodard, Chris M.

AU - Sun, Bruce

AU - Vilboux, Thierry

AU - Zimmer, Matthew

AU - Forero, Eliana

AU - Moroziewicz, Dorota N.

AU - Martinez, Hector

AU - Malicdan, May Christine V.

AU - Weiss, Keren A.

AU - Vensand, Lauren B.

AU - Dusenberry, Carmen R.

AU - Polus, Hannah

AU - Sy, Karla Therese L.

AU - Kahler, David J.

AU - Gahl, William A.

AU - Solomon, Susan L.

AU - Chang, Stephen

AU - Meissner, Alexander

AU - Eggan, Kevin

AU - Noggle, Scott A.

PY - 2015/8/28

Y1 - 2015/8/28

N2 - 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.

AB - 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.

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DO - 10.1038/nmeth.3507

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VL - 12

SP - 885

EP - 892

JO - Nature Methods

JF - Nature Methods

IS - 9

ER -

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

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