Frequency selectivity, multistability, and oscillations emerge from models of genetic regulatory systems
Frequency selectivity, multistability, and oscillations emerge from models of genetic regulatory systems
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DOI：
10.1152/ajpcell.1998.274.2.c531
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发表时间：
1998-02-01
影响因子：
5.5
通讯作者：
Byrne, JH
中科院分区：
文献类型：
--
作者：
Smolen, P;Baxter, DA;Byrne, JH
为了研究复杂的动态活动的基因调控系统的能力，我们开发了简单的动力学模型，将这些系统的已知功能。这些包括转录因子（TF）的自身调节和刺激依赖性磷酸化，TF的二聚化，串扰和反馈。最简单的模型表现出多个稳定的稳态，短暂的扰动可以在这些状态之间切换模型。例如，这种转变可以解释激素或神经递质的短暂脉冲如何引起持久的细胞反应。在稍微复杂一点的模型中，确定了振荡机制。另外，激活和抑制转录因子之间的竞争提供了一个合理的解释，最佳的刺激频率，使最大的转录。最近的实验比较了长期记忆形成的训练模式，并检查了重复刺激培养细胞中mRNA水平的变化，从而提出了这种最佳频率。在一般情况下，这里所示的计算方法，结合适当的实验，提供了一个概念框架，调查基因调控系统的功能。
To examine the capability of genetic regulatory systems for complex dynamic activity, we developed simple kinetic models that incorporate known features of these systems. These include autoregulation and stimulus-dependent phosphorylation of transcription factors (TFs), dimerization of TFs, crosstalk, and feedback. The simplest model manifested multiple stable steady states, and brief perturbations could switch the model between these states. Such transitions might explain, for example, how a brief pulse of hormone or neurotransmitter could elicit a long-lasting cellular response. In slightly more complex models, oscillatory regimes were identified. The addition of competition between activating and repressing TFs provided a plausible explanation for optimal stimulus frequencies that give maximal transcription. Such optimal frequencies are suggested by recent experiments comparing training paradigms for long-term memory formation and examining changes in mRNA levels in repetitively stimulated cultured cells. In general, the computational approach illustrated here, combined with appropriate experiments, provides a conceptual framework for investigating the function of genetic regulatory systems.