Department of Mathematics and International Center for Quantum and Molecular Structures, Shanghai University, China.
FEBS Open Bio. 2021 Jun;11(6):1799-1808. doi: 10.1002/2211-5463.13179. Epub 2021 May 27.
Many factors determine target gene expression dynamics under p53 pulsing. In this study, I sought to determine the mechanism by which duration, frequency, binding affinity and maximal transcription rate affect the expression dynamics of target genes. Using an analytical method to solve a simple model, I found that the fold change of target gene expression increases relative to the number of p53 pulses, and the optimal frequency, 0.18 h , from two real p53 pulses drives the maximal fold change with a decay rate of 0.18 h . Moreover, p53 pulses may also lead to a higher fold change than sustained p53. Finally, I discovered that a Hill-type equation, including these effect factors, can characterise target gene expression. The average error between the theoretical predictions and experiments was 23%. Collectively, this equation advances the understanding of transcription factor dynamics, where duration and frequency play a significant role in the fine regulation of target gene expression with higher binding affinity.
许多因素决定了 p53 脉冲下靶基因表达的动态变化。在这项研究中,我试图确定持续时间、频率、结合亲和力和最大转录速率如何影响靶基因的表达动态。使用一种分析方法来求解一个简单的模型,我发现靶基因表达的倍数变化相对于 p53 脉冲的数量增加,并且两个实际的 p53 脉冲的最优频率 0.18 h 以 0.18 h 的衰减率驱动最大倍数变化。此外,p53 脉冲可能会导致比持续的 p53 更高的倍数变化。最后,我发现包含这些影响因素的 Hill 型方程可以描述靶基因的表达。理论预测与实验之间的平均误差为 23%。总的来说,这个方程推进了对转录因子动力学的理解,其中持续时间和频率在靶基因表达的精细调控中起着重要作用,与更高的结合亲和力有关。