Furusawa Chikara, Kaneko Kunihiko
Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.
Biol Direct. 2009 May 15;4:17. doi: 10.1186/1745-6150-4-17.
During normal development, cells undergo a unidirectional course of differentiation that progressively decreases the number of cell types they can potentially become. Pluripotent stem cells can differentiate into several types of cells, but terminally differentiated cells cannot differentiate any further. A fundamental problem in stem cell biology is the characterization of the difference in cellular states, e.g., gene expression profiles, between pluripotent stem cells and terminally differentiated cells.
To address the problem, we developed a dynamical systems model of cells with intracellular protein expression dynamics and interactions with each other. According to extensive simulations, cells with irregular (chaotic) oscillations in gene expression dynamics have the potential to differentiate into other cell types. During development, such complex oscillations are lost successively, leading to a loss of pluripotency. These simulation results, together with recent single-cell-level measurements in stem cells, led us to the following hypothesis regarding pluripotency: Chaotic oscillation in the expression of some genes leads to cell pluripotency and affords cellular state heterogeneity, which is supported by itinerancy over quasi-stable states. Differentiation stabilizes these states, leading to a loss of pluripotency.
To test the hypothesis, it is crucial to measure the time course of gene expression levels at the single-cell level by fluorescence microscopy and fluorescence-activated cell sorting (FACS) analysis. By analyzing the time series of single-cell-level expression data, one can distinguish whether the variation in protein expression level over time is due only to stochasticity in expression dynamics or originates from the chaotic dynamics inherent to cells, as our hypothesis predicts. By further analyzing the expression in differentiated cell types, one can examine whether the loss of pluripotency is accompanied by a loss of oscillation.
Recovery of pluripotency from determined cells is a long-standing aspiration, from both scientific and clinical perspectives. Our hypothesis suggests a feasible route to recover the potential to differentiate, i.e., by increasing the variety of expressed genes to restore chaotic expression dynamics, as is consistent with the recent generation of induced pluripotent stem (iPS) cells.
在正常发育过程中,细胞经历单向分化过程,这一过程会逐渐减少它们可能分化成的细胞类型数量。多能干细胞可以分化为几种类型的细胞,但终末分化细胞则无法进一步分化。干细胞生物学中的一个基本问题是表征多能干细胞和终末分化细胞之间细胞状态的差异,例如基因表达谱。
为了解决这个问题,我们开发了一个细胞动力学系统模型,该模型考虑了细胞内蛋白质表达动力学以及细胞间的相互作用。根据大量模拟结果,基因表达动力学呈现不规则(混沌)振荡的细胞具有分化为其他细胞类型的潜力。在发育过程中,这种复杂振荡会相继消失,导致多能性丧失。这些模拟结果,连同近期在干细胞中进行的单细胞水平测量,使我们得出了关于多能性的以下假设:某些基因表达中的混沌振荡导致细胞多能性,并赋予细胞状态异质性,这由在准稳态上的遍历所支持。分化使这些状态稳定下来,导致多能性丧失。
为了检验该假设,通过荧光显微镜和荧光激活细胞分选(FACS)分析在单细胞水平测量基因表达水平的时间进程至关重要。通过分析单细胞水平表达数据的时间序列,就可以区分蛋白质表达水平随时间的变化仅仅是由于表达动力学中的随机性,还是如我们的假设所预测的那样源于细胞固有的混沌动力学。通过进一步分析分化细胞类型中的表达情况,就可以研究多能性的丧失是否伴随着振荡的丧失。
从科学和临床角度来看,从已确定的细胞中恢复多能性一直是人们长期以来的愿望。我们的假设提出了一条恢复分化潜力的可行途径,即通过增加表达基因的多样性来恢复混沌表达动力学,这与最近诱导多能干细胞(iPS细胞)的产生是一致的。