Pusuluri Sai Teja, Lang Alex H, Mehta Pankaj, Castillo Horacio E
Department of Physics and Astronomy and Nanoscale and Quantum Phenomena Institute, Ohio University, Athens, OH, 45701, United States of America. These authors contributed equally to this work.
Phys Biol. 2017 Dec 6;15(1):016001. doi: 10.1088/1478-3975/aa90e0.
Cellular reprogramming, the conversion of one cell type to another, induces global changes in gene expression involving thousands of genes, and understanding how cells globally alter their gene expression profile during reprogramming is an ongoing problem. Here we reanalyze time-course data on cellular reprogramming from differentiated cell types to induced pluripotent stem cells (iPSCs) and show that gene expression dynamics during reprogramming follow a simple 1D reaction coordinate. This reaction coordinate is independent of both the time it takes to reach the iPSC state as well as the details of the experimental protocol used. Using Monte-Carlo simulations, we show that such a reaction coordinate emerges from epigenetic landscape models where cellular reprogramming is viewed as a 'barrier-crossing' process between cell fates. Overall, our analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an 'optimal path' in gene expression space for reprogramming.
细胞重编程,即将一种细胞类型转变为另一种细胞类型,会引发涉及数千个基因的全基因组表达变化,而理解细胞在重编程过程中如何全局性地改变其基因表达谱仍是一个悬而未决的问题。在此,我们重新分析了从分化细胞类型到诱导多能干细胞(iPSC)的细胞重编程的时间进程数据,并表明重编程过程中的基因表达动态遵循一个简单的一维反应坐标。这个反应坐标既独立于达到iPSC状态所需的时间,也独立于所使用实验方案的细节。通过蒙特卡洛模拟,我们表明这样一个反应坐标源自表观遗传景观模型,在该模型中细胞重编程被视为细胞命运之间的“跨越障碍”过程。总体而言,我们的分析和模型表明,重编程过程中的基因表达动态遵循一条与重编程基因表达空间中“最优路径”概念一致的典型轨迹。