转录激活因子在果蝇早期胚胎中发挥着不同的动力学作用。

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Timothy T Harden, Ben J Vincent, Angela H DePace
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引用次数: 0

摘要

转录因子(tf)对基因表达的组合调控可能部分源于动力学协同作用,其中tf调节转录周期的不同步骤。动能协同作用要求tf发挥不同的动能作用。在这里,我们使用实时成像技术,通过将三种tf的结合位点引入到均匀跳过的条带2增强子中,来确定它们在果蝇胚胎中激活转录的动力学作用——zelda、Bicoid和stat92e。这些TFs影响不同的动力学参数集,它们的影响可以随着时间的推移而改变。三种tf均增加了转录活性核的比例;Zelda还缩短了进入转录的首次传代时间,并调节了转录事件之间的间隔。Stat92E也增加了活性转录的寿命。因此,不同的tf在激活转录方面可以发挥不同的动力学作用。这对理解调控DNA序列的组成和灵活性以及tf的生化功能具有重要意义。本文的透明同行评议过程记录包含在补充信息中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transcriptional activators in the early Drosophila embryo perform different kinetic roles.

Combinatorial regulation of gene expression by transcription factors (TFs) may in part arise from kinetic synergy-wherein TFs regulate different steps in the transcription cycle. Kinetic synergy requires that TFs play distinguishable kinetic roles. Here, we used live imaging to determine the kinetic roles of three TFs that activate transcription in the Drosophila embryo-Zelda, Bicoid, and Stat92E-by introducing their binding sites into the even-skipped stripe 2 enhancer. These TFs influence different sets of kinetic parameters, and their influence can change over time. All three TFs increased the fraction of transcriptionally active nuclei; Zelda also shortened the first-passage time into transcription and regulated the interval between transcription events. Stat92E also increased the lifetimes of active transcription. Different TFs can therefore play distinct kinetic roles in activating the transcription. This has consequences for understanding the composition and flexibility of regulatory DNA sequences and the biochemical function of TFs. A record of this paper's transparent peer review process is included in the supplemental information.

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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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