Zunder Eli R, Lujan Ernesto, Goltsev Yury, Wernig Marius, Nolan Garry P
Department of Microbiology and Immunology, Baxter Laboratory for Stem Cell Biology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Department of Pathology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
Cell Stem Cell. 2015 Mar 5;16(3):323-37. doi: 10.1016/j.stem.2015.01.015.
To analyze cellular reprogramming at the single-cell level, mass cytometry was used to simultaneously measure markers of pluripotency, differentiation, cell-cycle status, and cellular signaling throughout the reprogramming process. Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems. Although these systems varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry, they presented a common set of reprogramming landmarks. Early in the reprogramming process, Oct4(high)Klf4(high) cells transitioned to a CD73(high)CD104(high)CD54(low) partially reprogrammed state. Ki67(low) cells from this intermediate population reverted to a MEF-like phenotype, but Ki67(high) cells advanced through the M-E-T and then bifurcated into two distinct populations: an ESC-like Nanog(high)Sox2(high)CD54(high) population and a mesendoderm-like Nanog(low)Sox2(low)Lin28(high)CD24(high)PDGFR-α(high) population. The methods developed here for time-resolved, single-cell progression analysis may be used for the study of additional complex and dynamic systems, such as cancer progression and embryonic development.
为了在单细胞水平分析细胞重编程,在整个重编程过程中,采用质谱流式细胞术同时测量多能性、分化、细胞周期状态和细胞信号传导的标志物。对所得数据集进行时间分辨进程分析,以构建三个独立重编程系统的连续分子路线图。尽管这些系统在Oct4、Sox2、Klf4和c-Myc化学计量上有很大差异,但它们呈现出一组共同的重编程标志。在重编程过程早期,Oct4(高)Klf4(高)细胞转变为CD73(高)CD104(高)CD54(低)的部分重编程状态。来自这个中间群体的Ki67(低)细胞恢复为MEF样表型,但Ki67(高)细胞通过M-E-T阶段,然后分叉为两个不同的群体:一个类似胚胎干细胞的Nanog(高)Sox2(高)CD54(高)群体和一个中胚层样的Nanog(低)Sox2(低)Lin28(高)CD24(高)PDGFR-α(高)群体。这里开发的用于时间分辨单细胞进程分析的方法可用于研究其他复杂和动态系统,如癌症进展和胚胎发育。