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一种改良的携带反向四环素调控转录激活因子3的可重编程小鼠模型。

An improved reprogrammable mouse model harbouring the reverse tetracycline-controlled transcriptional transactivator 3.

作者信息

Alaei S, Knaupp A S, Lim S M, Chen J, Holmes M L, Änkö M L, Nefzger C M, Polo J M

机构信息

Department of Anatomy and Developmental Biology, Monash University, Wellington Road, Clayton, VIC 3800, Australia; Australian Regenerative Medicine Institute, Monash University, Wellington Road, Clayton, VIC 3800, Australia; Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Wellington Road, Clayton, VIC 3800, Australia.

Department of Anatomy and Developmental Biology, Monash University, Wellington Road, Clayton, VIC 3800, Australia; Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Wellington Road, Clayton, VIC 3800, Australia.

出版信息

Stem Cell Res. 2016 Jul;17(1):49-53. doi: 10.1016/j.scr.2016.05.008. Epub 2016 May 25.

DOI:10.1016/j.scr.2016.05.008
PMID:27558603
Abstract

Reprogrammable mouse models engineered to conditionally express Oct-4, Klf-4, Sox-2 and c-Myc (OKSM) have been instrumental in dissecting molecular events underpinning the generation of induced pluripotent stem cells. However, until now these models have been reported in the context of the m2 reverse tetracycline-controlled transactivator, which results in low reprogramming efficiency and consequently limits the number of reprogramming intermediates that can be isolated for downstream profiling. Here, we describe an improved OKSM mouse model in the context of the reverse tetracycline-controlled transactivator 3 with enhanced reprogramming efficiency (>9-fold) and increased numbers of reprogramming intermediate cells albeit with similar kinetics, which we believe will facilitate mechanistic studies of the reprogramming process.

摘要

经过工程改造以条件性表达Oct-4、Klf-4、Sox-2和c-Myc(OKSM)的可重编程小鼠模型,在剖析诱导多能干细胞产生背后的分子事件方面发挥了重要作用。然而,到目前为止,这些模型是在m2反向四环素控制的反式激活因子背景下报道的,这导致重编程效率低下,从而限制了可分离用于下游分析的重编程中间体的数量。在这里,我们描述了一种在反向四环素控制的反式激活因子3背景下的改进型OKSM小鼠模型,其重编程效率提高(>9倍),重编程中间体细胞数量增加,尽管动力学相似,我们认为这将有助于重编程过程的机制研究。

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