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首页> 外文期刊>BioSystems >Cell-to-cell diversification in ERBB-RAS-MAPK signal transduction that produces cell-type specific growth factor responses
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Cell-to-cell diversification in ERBB-RAS-MAPK signal transduction that produces cell-type specific growth factor responses

机译:ERBB-RAS-MAPK信号转导中的细胞对细胞多样化,产生细胞型特异性生长因子响应

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Growth factors regulate cell fates, including their proliferation, differentiation, survival, and death, according to the cell type. Even when the response to a specific growth factor is deterministic for collective cell behavior, significant levels of fluctuation are often observed between single cells. Statistical analyses of single-cell responses provide insights into the mechanism of cell fate decisions but very little is known about the distributions of the internal states of cells responding to growth factors. Using multi-color immunofluorescent staining, we have here detected the phosphorylation of seven elements in the early response of the ERBB-RAS-MAPK system to two growth factors. Among these seven elements, five were analyzed simultaneously in distinct combinations in the same single cells. Although principle component analysis suggested cell-type and input specific phosphorylation patterns, cell-to-cell fluctuation was large. Mutual information analysis suggested that each cell type uses multitrack (bush-like) signal transduction pathways under conditions in which clear fate changes have been reported. The clustering of single-cell response patterns indicated that the fate change in a cell population correlates with the large entropy of the response, suggesting a bet-hedging strategy is used in decision making. A comparison of true and randomized datasets further indicated that this large variation is not produced by simple reaction noise, but is defined by the properties of the signal-processing network.
机译:根据细胞类型,生长因子调节细胞命令,包括它们的增殖,分化,生存和死亡。即使当对特定生长因子的反应是集体细胞行为的确定性,在单细胞之间通常观察到显着的波动。单细胞反应的统计分析提供了对细胞命运决策机制的见解,但对响应生长因子的细胞内部状态的分布很少。使用多色免疫荧光染色,我们在此处检测了ErbB-RAS-MAPK系统早期响应的七种元素的磷酸化到两个生长因子。在这七种元素中,在同一单细胞中的不同组合中同时分析五个。尽管原理成分分析建议细胞型和输入特异性磷酸化图案,但细胞对细胞波动大。互信息分析表明,每个细胞类型使用多纹(类似灌木)信号转导途径在报告清晰的命运变化的条件下。单细胞响应模式的聚类表明,细胞群中的命运变化与响应的大熵相关,建议在决策中使用Bet-Hedging策略。真实和随机数据集的比较进一步表明,不通过简单的反应噪声产生这种大的变化,而是由信号处理网络的性质限定。

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