Tuning promoter strength through RNA polymerase binding site design in Escherichia coli.-猫眼课题宝

DOI：

10.1371/journal.pcbi.1002811

发表时间：

2012

期刊：

PLoS computational biology

影响因子：

4.3

通讯作者：

中科院分区：

生物学2区

文献类型：

作者：

Brewster RC;Jones DL;Phillips R

来源链接：

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521663/?report=classic

合成生物学的首要目标之一是能够随意调整转录网络以达到目标表达水平。作为朝着这个方向迈出的一步，我们已经构建了一组独特的结合位点。大肠杆菌RNA聚合酶（RNAP）全酶，设计使用一个模型的序列依赖性结合能结合转录的热力学模型，以产生一个目标水平的基因表达。该启动子组使我们能够确定mRNA分子或蛋白质产物的绝对数量与以能量单位测量的预测启动子结合能之间的对应关系。这些结合位点在组成型基因表达的数量级上平均粘附于预测的基因表达水平，在蛋白质和mRNA拷贝数的因子内。有了这些启动子，我们将它们置于细菌阻遏物的调控下，并再次表明测量和预测的表达水平之间存在严格的对应关系，证明了启动子可转移到替代的调控环境中。特别地，我们的热力学模型预测了在一系列阻遏物浓度下从我们的启动子的表达，所述阻遏物浓度在每个细胞几个到每个细胞以上之间。在使用来自未调节的启动子的数据校正预测的聚合酶结合强度之后，热力学模型准确地预测了简单阻遏菌株的表达。模块化启动子设计的演示，其中电路的部分（如RNAP/TF结合强度和转录因子拷贝数）可以独立地从库存列表中选择并组合以给出可预测的结果，作为用于合成生物学的工程工具具有重要意义。控制给定基因表达的最基本的调节参数之一是其启动子的强度。但是控制启动子强度的序列规则是什么呢？最近的高通量诱变实验提出了一种用于构建将序列映射到蛋白质-DNA结合能的能量函数的改进方法。我们使用这种能量函数结合热力学模型来故意设计不同的启动子，其平均表达具有超过三个数量级的差异，并在mRNA和蛋白质水平上测量所得的表达水平以测试这种设计策略。所设计的启动子用于替代的监管架构，现在可以作为基础的基因表达的均值和噪声如何依赖于已受到进化和/或人类变化的监管参数的系统检查。

One of the paramount goals of synthetic biology is to have the ability to tune transcriptional networks to targeted levels of expression at will. As a step in that direction, we have constructed a set of unique binding sites for E. coli RNA Polymerase (RNAP) holoenzyme, designed using a model of sequence-dependent binding energy combined with a thermodynamic model of transcription to produce a targeted level of gene expression. This promoter set allows us to determine the correspondence between the absolute numbers of mRNA molecules or protein products and the predicted promoter binding energies measured in energy units. These binding sites adhere on average to the predicted level of gene expression over orders of magnitude in constitutive gene expression, to within a factor of in both protein and mRNA copy number. With these promoters in hand, we then place them under the regulatory control of a bacterial repressor and show that again there is a strict correspondence between the measured and predicted levels of expression, demonstrating the transferability of the promoters to an alternate regulatory context. In particular, our thermodynamic model predicts the expression from our promoters under a range of repressor concentrations between several per cell up to over per cell. After correcting the predicted polymerase binding strength using the data from the unregulated promoter, the thermodynamic model accurately predicts the expression for the simple repression strains to within . Demonstration of modular promoter design, where parts of the circuit (such as RNAP/TF binding strength and transcription factor copy number) can be independently chosen from a stock list and combined to give a predictable result, has important implications as an engineering tool for use in synthetic biology. One of the most fundamental tuning parameters governing expression of a given gene is the strength of its promoter. But what are the sequence rules that govern promoter strength? Recent high throughput mutagenesis experiments present an improved method for constructing an energy function that maps sequence to protein-DNA binding energy. We use this energy function combined with a thermodynamic model to deliberately design different promoters with over three orders of magnitude difference in their mean expression, and measure the resulting level of expression at both the mRNA and protein level to test this design strategy. The designed promoters are used in an alternate regulatory architecture and can now serve as the basis for the systematic examination of how both the mean and noise in gene expression depend upon the regulatory parameters that have been subject to evolutionary and/or human change.