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Hill 型方程可以预测由 p53 脉冲驱动的靶基因表达。

A Hill type equation can predict target gene expression driven by p53 pulsing.

机构信息

Department of Mathematics and International Center for Quantum and Molecular Structures, Shanghai University, China.

出版信息

FEBS Open Bio. 2021 Jun;11(6):1799-1808. doi: 10.1002/2211-5463.13179. Epub 2021 May 27.

Abstract

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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46af/8167869/1c04cd5f710d/FEB4-11-1799-g003.jpg

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