Binary cell fate decision as high-dimensional critical state transition

During commitment of a multipotent stem or progenitor cell to a particular lineage, a large number of genes alter their expression in a coordinated manner orchestrated by the gene regulatory network (GRN). The constraints imposed by the GRN govern how cells move in the high-dimensional gene expression state space and can be understood as a dynamical system in which phenotypic cell states (cell types) are attractors that stabilize the cell-type characteristic gene expression pattern against molecular noise. Despite insights from various theoretical models, it remains elusive how multipotent cells, when committing to a specific lineage, exit their attractor and enter a new distinct attractor. Here we show, using single-cell resolution monitoring of transcript patterns by qPCR that commitment of multipotent blood progenitor cells to either the erythroid or the myeloid lineage is preceded by a destabilization of the progenitors’ attractor state and a slowing-down of relaxation of cells from outlier states, indicating a critical state transition (“tipping point”). The high-dimensionality of the system (many genes) and availability of individual trajectories of a large ensemble of systems (many cells) affords a novel signature for critical transition which can be predicted from theory: Decrease of correlation between cells and concomitant increase of correlation between genes as the cell population approaches the tipping point. Consistent with a destabilizing bifurcation that simultaneously opens access to the erythroid and myeloid attractors, differentiation signal for either lineage caused some cells to commit to the “wrong” fate; moreover providing conflicting signals resulted in a delayed decision at the bifurcation point that however was ultimately resolved by commitment to one fate. These results suggest that the theoretical framework of “early-warning signs” and critical transitions can be applied to ensembles of high-dimensional systems, offering a formal tool for analyzing single-cell omics data beyond current descriptive computational pattern recognition. Mouse blood progenitor cells (EML cell line) was exposed to EPO, IL-3/GM-CSF or a mixture of both cytokines and gene expression change was measured in sorted subpopulations wrt Sca1 progenitor surface marker expression. In total, there was 4 conditions (including control), three time points (including d0) and 20 samples (10 samples in duplicates) were analyzed. Two independent experiments were performed for each condition. The untreated progenitor cell population was used as control.

当多能干细胞或祖细胞向特定谱系定型时，大量基因会在基因调控网络（gene regulatory network, GRN）的协同调控下以协调一致的方式改变其表达水平。基因调控网络施加的约束决定了细胞在高维基因表达状态空间中的运动规律，该过程可被视为一个动力学系统：其中表型细胞状态（即细胞类型）作为吸引子，能够稳定细胞类型特有的基因表达模式以抵御分子噪声的干扰。尽管各类理论模型已提供诸多研究洞见，但多能细胞在向特定谱系定型时，如何脱离原有吸引子并进入新的独特吸引子，这一问题至今仍未得到清晰阐释。本研究通过定量PCR（qPCR）对转录组模式进行单细胞分辨率监测，结果显示：多能造血祖细胞向红系或髓系谱系定型前，其祖细胞的吸引子状态会发生去稳定化，且细胞从异常状态恢复松弛的速率会减慢，这提示存在一次临界状态转换（tipping point）。该系统兼具高维度（基因数量庞大）与包含大量独立系统个体轨迹（即众多细胞）的特点，这为临界转换提供了一种可从理论推导得出的全新特征：当细胞群体趋近临界点时，细胞间的相关性会下降，而基因间的相关性则会同步上升。与同时开放红系与髓系吸引子的去稳定化分岔相符，任一谱系的分化信号都会导致部分细胞错误地向“非对应”命运定型；此外，同时施加相互冲突的信号会使细胞在分岔点处的决策出现延迟，但最终仍会完成向其中一种命运的定型。上述结果表明，“早期预警信号”与临界转换的理论框架可应用于高维系统的集合分析，为单细胞组学数据的分析提供了一种超越当前描述性计算模式识别的正式分析工具。本研究以小鼠造血祖细胞（EML细胞系）为研究对象，分别将其暴露于促红细胞生成素（EPO）、白细胞介素-3/粒细胞-巨噬细胞集落刺激因子（IL-3/GM-CSF）或两种细胞因子的混合液中，并通过分选基于Sca1祖细胞表面标志物表达的亚群，检测各亚群的基因表达变化。本研究共设置4种实验条件（含对照组）、3个时间点（含第0天，d0），共分析20个样本（其中10个样本设置为生物学重复）。所有实验条件均独立重复两次，未处理的祖细胞群体作为对照。