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非整合重编程方法的比较。

A comparison of non-integrating reprogramming methods.

作者信息

Schlaeger Thorsten M, Daheron Laurence, Brickler Thomas R, Entwisle Samuel, Chan Karrie, Cianci Amelia, DeVine Alexander, Ettenger Andrew, Fitzgerald Kelly, Godfrey Michelle, Gupta Dipti, McPherson Jade, Malwadkar Prerana, Gupta Manav, Bell Blair, Doi Akiko, Jung Namyoung, Li Xin, Lynes Maureen S, Brookes Emily, Cherry Anne B C, Demirbas Didem, Tsankov Alexander M, Zon Leonard I, Rubin Lee L, Feinberg Andrew P, Meissner Alexander, Cowan Chad A, Daley George Q

机构信息

1] Division of Pediatric Hematology/Oncology, Boston Children's Hospital, Dana-Farber Cancer Institute, Boston, Massachusetts, USA. [2] Harvard Stem Cell Institute, Cambridge, Massachusetts, USA.

Harvard Stem Cell Institute, Cambridge, Massachusetts, USA.

出版信息

Nat Biotechnol. 2015 Jan;33(1):58-63. doi: 10.1038/nbt.3070. Epub 2014 Dec 1.

Abstract

Human induced pluripotent stem cells (hiPSCs) are useful in disease modeling and drug discovery, and they promise to provide a new generation of cell-based therapeutics. To date there has been no systematic evaluation of the most widely used techniques for generating integration-free hiPSCs. Here we compare Sendai-viral (SeV), episomal (Epi) and mRNA transfection mRNA methods using a number of criteria. All methods generated high-quality hiPSCs, but significant differences existed in aneuploidy rates, reprogramming efficiency, reliability and workload. We discuss the advantages and shortcomings of each approach, and present and review the results of a survey of a large number of human reprogramming laboratories on their independent experiences and preferences. Our analysis provides a valuable resource to inform the use of specific reprogramming methods for different laboratories and different applications, including clinical translation.

摘要

人诱导多能干细胞(hiPSC)在疾病建模和药物发现中很有用,并且有望提供新一代基于细胞的疗法。迄今为止,尚未对用于生成无整合hiPSC的最广泛使用的技术进行系统评估。在这里,我们使用多种标准比较了仙台病毒(SeV)、游离型(Epi)和mRNA转染mRNA方法。所有方法都能产生高质量的hiPSC,但在非整倍体率、重编程效率、可靠性和工作量方面存在显著差异。我们讨论了每种方法的优缺点,并展示和回顾了对大量人类重编程实验室关于其独立经验和偏好的调查结果。我们的分析为不同实验室和不同应用(包括临床转化)使用特定重编程方法提供了有价值的参考资源。

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