Studying stochasticity in eukaryotic gene expression using novel tools of synthetic biology modelling and analytical science

使用合成生物学建模和分析科学的新工具研究真核基因表达的随机性

• 批准号: BB/I008349/1
• 负责人: John McCarthy
• 金额: $ 146.57万
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FI008349%2F1
• 关键词: Studying; stochasticity; eukaryotic; gene; expression

The information contained in the genes of living cells has to be converted into cellular components that form structures and enable biochemical reactions to take place. This process is called gene expression and it is vital to all known life. Gene expression comprises two main synthetic steps, called transcription and translation. In transcription, the information in the DNA sequences of the genes is converted into equivalent sequences in so-called messenger RNA (mRNA) molecules. In translation, the mRNA molecules are 'read' by a large molecular structure called the ribosome, which uses the information to dictate the synthesis of proteins. The proteins synthesised in this way have to fold into a number of types of three-dimensional structure in order to become active. However, processes like gene expression and signalling in biology are not entirely accurate at the molecular level. Indeed, we now realise that one of the wonders of cellular systems is how they cope with the fluctuations in the functioning of their molecular processes. Indeed, these fluctuations actually play important roles in regulation, stress responses and other processes in biology. Our project will study how the fluctuations that occur at different steps in gene expression affect the performance of the system. To do this, we will use a gene expression pathway that we have partly built ourselves using synthetic biology techniques. This pathway has been made to interact in only a very limited way with other cellular processes so that when we manipulate it, this has no adverse effects on the cells and the responses are limited to the pathway itself. We will examine how each of the steps of gene expression outlined above contribute to the fluctuations in the gene expression pathway, and also how these respective contributions add up overall. We will do this using novel analytical methods and imaging. Microfluidics will be used to separate individual cells so that we can study changes in gene expression in each cell over time. In parallel to the experimental work, we will use computational modelling to help us understand how the system works and to help us design experiments (to test our models). Finally, we will investigate whether the fluctuations in the functioning of the system can be suppressed using synthetic genetic circuits that are known to be commonly used in natural biological systems. In this way, we will learn how noise at the molecular level can be prevented from becoming damaging to the cell. The theoretical and experimental technologies developed and applied in this project will be of value to a wide spectrum of researchers in academia and industry.

活细胞基因中包含的信息必须转化为形成结构并使生化反应能够发生的细胞成分。这个过程被称为基因表达，它对所有已知的生命都至关重要。基因表达包括两个主要的合成步骤，称为转录和翻译。在转录过程中，基因的DNA序列中的信息被转换成所谓信使RNA（mRNA）分子中的等同序列。在翻译过程中，mRNA分子被称为核糖体的大分子结构“读取”，核糖体使用信息来决定蛋白质的合成。以这种方式合成的蛋白质必须折叠成许多类型的三维结构才能变得活跃。然而，生物学中的基因表达和信号传导等过程在分子水平上并不完全准确。事实上，我们现在意识到，细胞系统的奇迹之一是它们如何科普分子过程功能的波动。事实上，这些波动实际上在调节、应激反应和生物学的其他过程中发挥着重要作用。我们的项目将研究在基因表达的不同步骤发生的波动如何影响系统的性能。为了做到这一点，我们将使用一种基因表达途径，这是我们利用合成生物学技术自己建立的。这条通路只能以非常有限的方式与其他细胞过程相互作用，因此当我们操纵它时，对细胞没有不利影响，反应仅限于通路本身。我们将研究上面概述的基因表达的每个步骤如何影响基因表达途径的波动，以及这些各自的贡献如何总体相加。我们将使用新的分析方法和成像来做到这一点。微流体将用于分离单个细胞，以便我们可以研究每个细胞中基因表达随时间的变化。在实验工作的同时，我们将使用计算建模来帮助我们理解系统的工作原理，并帮助我们设计实验（以测试我们的模型）。最后，我们将研究是否可以使用已知在自然生物系统中常用的合成遗传电路来抑制系统功能的波动。通过这种方式，我们将了解如何在分子水平上防止噪音对细胞造成损害。在这个项目中开发和应用的理论和实验技术将对学术界和工业界的广泛研究人员具有价值。

项目成果

Translation initiation events on structured eukaryotic mRNAs generate gene expression noise.

• DOI: 10.1093/nar/gkx430
• 发表时间: 2017-06-20
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Dacheux E;Malys N;Meng X;Ramachandran V;Mendes P;McCarthy JEG
• 通讯作者: McCarthy JEG

Minimum-noise production of translation factor eIF4G maps to a mechanistically determined optimal rate control window for protein synthesis.

• DOI: 10.1093/nar/gkw1194
• 发表时间: 2017-01-25
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Meng X;Firczuk H;Pietroni P;Westbrook R;Dacheux E;Mendes P;McCarthy JE
• 通讯作者: McCarthy JE