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通过合成启动子精细调控细菌中的基因表达。

Fine-Tuning Gene Expression in Bacteria by Synthetic Promoters.

机构信息

Department of Vaccine Technology, Vaccine Institute, Hacettepe University, Ankara, Türkiye.

出版信息

Methods Mol Biol. 2024;2844:179-195. doi: 10.1007/978-1-0716-4063-0_12.

Abstract

Promoters are key genetic elements in the initiation and regulation of gene expression. A limited number of natural promoters has been described for the control of gene expression in synthetic biology applications. Therefore, synthetic promoters have been developed to fine-tune the transcription for the desired amount of gene product. Mostly, synthetic promoters are characterized using promoter libraries that are constructed via mutagenesis of promoter sequences. The strength of promoters in the library is determined according to the expression of a reporter gene such as gfp encoding green fluorescent protein. Gene expression can be controlled using inducers. The majority of the studies on gram-negative bacteria are conducted using the expression system of the model organism Escherichia coli while that of the model organism Bacillus subtilis is mostly used in the studies on gram-positive bacteria. Additionally, synthetic promoters for the cyanobacteria, which are phototrophic microorganisms, are evaluated, especially using the model cyanobacterium Synechocystis sp. PCC 6803. Moreover, a variety of algorithms based on machine learning methods were developed to characterize the features of promoter elements. Some of these in silico models were verified using in vitro or in vivo experiments. Identification of novel synthetic promoters with improved features compared to natural ones contributes much to the synthetic biology approaches in terms of fine-tuning gene expression.

摘要

启动子是基因表达起始和调控的关键遗传元件。在合成生物学应用中,已经描述了少量用于控制基因表达的天然启动子。因此,已经开发了合成启动子来微调转录以获得所需量的基因产物。大多数情况下,通过对启动子序列进行诱变来构建启动子文库来表征合成启动子。文库中启动子的强度根据报告基因(如编码绿色荧光蛋白的 GFP)的表达来确定。可以使用诱导物来控制基因表达。大多数关于革兰氏阴性菌的研究都是使用模式生物大肠杆菌的表达系统进行的,而模型生物枯草芽孢杆菌的研究则主要用于革兰氏阳性菌的研究。此外,还评估了用于光合微生物蓝藻的合成启动子,特别是使用模式蓝藻集胞藻 PCC 6803。此外,还开发了基于机器学习方法的各种算法来表征启动子元件的特征。其中一些基于计算机的模型已经通过体外或体内实验进行了验证。与天然启动子相比,新型合成启动子的鉴定具有改进的特征,这对基因表达的微调等合成生物学方法有很大贡献。

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