Predictive modeling reveals that higher-order cooperativity drives transcriptional repression in a synthetic developmental enhancer.
Predictive modeling reveals that higher-order cooperativity drives transcriptional repression in a synthetic developmental enhancer.
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DOI：
10.7554/elife.73395
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发表时间：
2022-12-12
期刊：
影响因子：
7.7
通讯作者：
Garcia HG
中科院分区：
文献类型：
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作者：
Kim YJ;Rhee K;Liu J;Jeammet S;Turner MA;Small SJ;Garcia HG
定量生物学的一个挑战是根据输入转录因子模式的知识和这些转录因子在调控DNA上的结合位点的安排来预测基因表达的输出模式。我们测试了广泛的热力学模型是否可以用来推断描述简单调控结构的参数，这些参数可以在早期果蝇胚胎中Runt转录抑制的背景下为更复杂的增强子提供无参数预测。通过调节增强子中Runt结合位点的数量和位置，并使用实时成像量化由此产生的转录活性，我们发现热力学模型要求多个分子参与者之间的高阶协作性。这种高阶的协同性反映了真核生物转录调控的组合复杂性，不能从更简单的调控结构中确定，这突出了对真核生物转录调控的预测性理解所面临的挑战，并呼吁采用定量剖析其分子性质的方法。
A challenge in quantitative biology is to predict output patterns of gene expression from knowledge of input transcription factor patterns and from the arrangement of binding sites for these transcription factors on regulatory DNA. We tested whether widespread thermodynamic models could be used to infer parameters describing simple regulatory architectures that inform parameter-free predictions of more complex enhancers in the context of transcriptional repression by Runt in the early fruit fly embryo. By modulating the number and placement of Runt binding sites within an enhancer, and quantifying the resulting transcriptional activity using live imaging, we discovered that thermodynamic models call for higher-order cooperativity between multiple molecular players. This higher-order cooperativity captures the combinatorial complexity underlying eukaryotic transcriptional regulation and cannot be determined from simpler regulatory architectures, highlighting the challenges in reaching a predictive understanding of transcriptional regulation in eukaryotes and calling for approaches that quantitatively dissect their molecular nature.
影响因子：
--
作者：
Pan, Yuanwang;Rauskolb, Cordelia;Irvine, Kenneth D
通讯作者：
Irvine, Kenneth D
从头开始建筑增强剂：一种合成生物学方法。
影响因子：
64.5
作者：
Amit R;Garcia HG;Phillips R;Fraser SE
通讯作者：
Fraser SE