Hill-Type方程揭示了p53脉冲主导的靶蛋白表达调控原理

IF 2 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Xiaomin Shi
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引用次数: 0

摘要

中心法则指示了基因表达途径的基本方向。对于活化的基因表达,从转录因子(tf)与DNA结合到蛋白质合成的各种环节之间的定量关系仍然不清楚和有争议。目前的共识是,在稳定状态下,蛋白质水平在很大程度上取决于mRNA水平。我们怎样才能找到这个稳定状态呢?以p53为例,基于之前发现的表征p53脉冲作用下mRNA表达的hill型方程,我证明了同样的方程可以用来描述靶蛋白表达的平均稳态。因此,在稳态下,TFs脉冲作用下mRNA和蛋白表达的平均折叠变化相同。这一共识已得到成功证明。对于p53靶基因BAX, mRNA和蛋白表达的倍数变化分别为1.40和1.28;采用hill型方程计算mRNA和蛋白的表达倍数变化均为1.35。因此,利用这个方程,我们不仅可以微调基因表达,还可以从转录组预测蛋白质组。此外,通过引入两个定量指标,我们可以确定蛋白质表达的积累程度和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Hill-Type Equation Reveals the Regulatory Principle of Target Protein Expression Led by p53 Pulsing

The Hill-Type Equation Reveals the Regulatory Principle of Target Protein Expression Led by p53 Pulsing

The Hill-Type Equation Reveals the Regulatory Principle of Target Protein Expression Led by p53 Pulsing

The Hill-Type Equation Reveals the Regulatory Principle of Target Protein Expression Led by p53 Pulsing

The Hill-Type Equation Reveals the Regulatory Principle of Target Protein Expression Led by p53 Pulsing

The central dogma indicates the basic direction of gene expression pathways. For activated gene expression, the quantitative relationship between various links from the binding of transcription factors (TFs) to DNA to protein synthesis remains unclear and debated. There is consensus that at a steady state, protein levels are largely determined by the mRNA level. How can we find this steady state? Taking p53 as an example, based on the previously discovered Hill-type equation that characterizes mRNA expression under p53 pulsing, I proved that the same equation can be used to describe the average steady state of target protein expression. Therefore, at steady state, the average fold changes in mRNA and protein expression under TFs pulsing were the same. This consensus has been successfully demonstrated. For the p53 target gene BAX, the observed fold changes in mRNA and protein expression were 1.40 and 1.28, respectively; the fold changes in mRNA and protein expression calculated using the Hill-type equation were both 1.35. Therefore, using this equation, we can not only fine-tune gene expression, but also predict the proteome from the transcriptome. Furthermore, by introducing two quantitative indicators, we can determine the degree of accumulation and stability of protein expression.

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来源期刊
FASEB bioAdvances
FASEB bioAdvances Multiple-
CiteScore
5.40
自引率
3.70%
发文量
56
审稿时长
10 weeks
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