共 44 条
How Transcription Factors Binding Stimulates Transcriptional Bursting
被引:1
作者:

Mondal, Anupam
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h-index: 0
机构:
Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA
Rice Univ, Dept Chem, Houston, TX 77005 USA Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA

Kolomeisky, Anatoly B.
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h-index: 0
机构:
Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA
Rice Univ, Dept Chem, Houston, TX 77005 USA
Rice Univ, Dept Chem & Biomol Engn, Houston, TX 77005 USA Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA
机构:
[1] Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA
[2] Rice Univ, Dept Chem, Houston, TX 77005 USA
[3] Rice Univ, Dept Chem & Biomol Engn, Houston, TX 77005 USA
来源:
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
|
2024年
/
15卷
/
34期
关键词:
GENE-EXPRESSION;
TIME;
DNA;
DYNAMICS;
MECHANISMS;
KINETICS;
D O I:
10.1021/acs.jpclett.4c02050
中图分类号:
O64 [物理化学(理论化学)、化学物理学];
学科分类号:
070304 ;
081704 ;
摘要:
Transcription is a fundamental biological process of transferring genetic information which often occurs in stochastic bursts when periods of intense activity alternate with quiescent phases. Recent experiments identified strong correlations between the association of transcription factors (TFs) to gene promoters on DNA and transcriptional activity. However, the underlying molecular mechanisms of this phenomenon remain not well understood. Here, we present a theoretical framework that allowed us to investigate how binding dynamics of TF influences transcriptional bursting. Our minimal theoretical model incorporates the most relevant physical-chemical features, including TF exchange among multiple binding sites at gene promoters and TF association/dissociation dynamics. Using analytical calculations supported by Monte Carlo computer simulations, it is demonstrated that transcriptional bursting dynamics depends on the strength of TF binding and the number of binding sites. Stronger TF binding affinity prolongs burst duration but reduces variability, while an optimal number of binding sites maximizes transcriptional noise, facilitating cellular adaptation. Our theoretical method explains available experimental observations quantitatively, confirming the model's predictive accuracy. This study provides important insights into molecular mechanisms of gene expression and regulation, offering a new theoretical tool for understanding complex biological processes.
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收藏
页码:8781 / 8789
页数:9
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