Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence
Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence
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DOI：
10.1073/pnas.1004290107
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发表时间：
2010-05-18
影响因子：
11.1
通讯作者：
Cox, Edward C.
中科院分区：
文献类型：
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作者：
Kinney, Justin B.;Murugan, Anand;Cox, Edward C.
细胞利用蛋白质- dna和蛋白质-蛋白质相互作用来调节转录。然而，由于缺乏定量表征活细胞中特定启动子和增强子处发生的相互作用的方法，对这一过程的生物物理学理解受到限制。在这里，我们展示了如何通过一个简单的实验来揭示这些生物物理信息，在这个实验中，部分突变的调控序列库根据它们在体内的转录活性进行划分，然后进行大规模测序。本实验产生的序列数据的计算分析可以提供精确的定量信息，了解特定结合位点上的调节蛋白如何协同工作以调节转录。这种在面对实验噪声时可靠地提取有关调控生物物理学的精确信息的能力，是由最近确定的似然和互信息之间的关系所实现的。将我们的实验和计算技术应用于大肠杆菌lac启动子，我们证明了重新识别调节蛋白结合位点的能力，确定结合这些位点的蛋白质的序列依赖结合能，重要的是，测量RNA聚合酶和dna结合转录因子之间的体内相互作用能。我们的方法提供了一种普遍适用的方法，通过特定的调控序列来表征转录调控的生物物理基础。我们的方法的原理也可以应用于分子生物学中的许多其他问题。
Cells use protein-DNA and protein-protein interactions to regulate transcription. A biophysical understanding of this process has, however, been limited by the lack of methods for quantitatively characterizing the interactions that occur at specific promoters and enhancers in living cells. Here we show how such biophysical information can be revealed by a simple experiment in which a library of partially mutated regulatory sequences are partitioned according to their in vivo transcriptional activities and then sequenced en masse. Computational analysis of the sequence data produced by this experiment can provide precise quantitative information about how the regulatory proteins at a specific arrangement of binding sites work together to regulate transcription. This ability to reliably extract precise information about regulatory biophysics in the face of experimental noise is made possible by a recently identified relationship between likelihood and mutual information. Applying our experimental and computational techniques to the Escherichia coli lac promoter, we demonstrate the ability to identify regulatory protein binding sites de novo, determine the sequence-dependent binding energy of the proteins that bind these sites, and, importantly, measure the in vivo interaction energy between RNA polymerase and a DNA-bound transcription factor. Our approach provides a generally applicable method for characterizing the biophysical basis of transcriptional regulation by a specified regulatory sequence. The principles of our method can also be applied to a wide range of other problems in molecular biology.