Feedback control of translation termination in yeast

酵母翻译终止的反馈控制

• 批准号: EP/E057012/1
• 负责人: J Krishnan
• 金额: $ 11.78万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FE057012%2F1
• 关键词: Feedback; control; translation; termination; yeast

At the cellular level, all life is dependent upon using the genetic information stored in DNA to make proteins. These proteins, through their action as catalysts, conduct the biochemical reactions in the cell. In order to make proteins, genetic information at the DNA level is first copied into a second, chain-like molecule, called mRNA. Finally, the genetic information now encoded within the mRNA is then read, or 'translated', into protein by a complex biochemical assembly called a ribosome.The process of translation is itself extremely complex, but essentially can be divided into three phases; initiation, where the ribosome joins the mRNA to start translation; elongation, where the mRNA genetic information is read to make the protein; and termination, when the ribosome leaves the mRNA. It is this last stage that forms the focus of this research. It is crucial that translation is terminated efficiently. If the ribosome stops too early, an incomplete protein is made, which will be non-functional. Crucially, such 'premature' stop events can be caused by mutations, such as some of the DNA defects underlying diseases like cystic fibrosis. In many cystic fibrosis patients, the DNA mutation in the cystic fibrosis gene, when copied into mRNA and translated by the ribosome, causes a short, non-functional protein to be made. The absence of the full-length product produces the symptoms of the disease. Understanding the way in which DNA mutations direct the manufacture of truncated proteins requires a fundamental knowledge of the termination stage of translation, and of the way that the ribosome responds to mutations in the genetic information. The complexity of process demands that new tools are developed to investigate the biochemistry that underpins the process. One such set of tools, mathematical and computational modelling, can be used to generate a quantitative description of translation and the termination step. Once modelled, translation can be studied using computer simulations, in parallel with laboratory experimental investigations. Modelling of biochemical processes is an emerging field that offers exciting prospects for understanding the complexity of cellular control circuits. In this proposal, biologists will work collaboratively with control/system engineers to model the translation process, including the termination step. The termination process of the model organism baker's yeast will be studied, due to the similarity of the process in yeast and human cells. In addition, there exist a series of yeast mutants that highlight feedback control of the translation termination step. Study of these mutants, and of how the feedback loop is controlled, provides an exciting opportunity to investigate many of the parameters that control protein synthesis and that regulate the length of all proteins in the cell. This understanding can, in the longer term, be applied to the study of the effects of human genetic diseases like cystic fibrosis.

在细胞水平上，所有生命都依赖于使用存储在DNA中的遗传信息来制造蛋白质。这些蛋白质，通过它们作为催化剂的作用，在细胞中进行生化反应。为了制造蛋白质，DNA水平的遗传信息首先被复制到第二个链状分子中，称为mRNA。最后，mRNA中编码的遗传信息被称为核糖体的复杂生物化学组合读取或“翻译”成蛋白质。翻译过程本身极其复杂，但基本上可分为三个阶段：起始，核糖体与mRNA结合开始翻译;延伸，mRNA遗传信息被读取以制造蛋白质;当核糖体离开mRNA时终止。正是这最后一个阶段形成了本研究的重点。关键是要高效地终止翻译。如果核糖体过早停止，就会产生不完整的蛋白质，这将是无功能的。至关重要的是，这种“过早”停止事件可能是由突变引起的，例如囊性纤维化等疾病的一些DNA缺陷。在许多囊性纤维化患者中，囊性纤维化基因中的DNA突变，当复制成mRNA并由核糖体翻译时，会导致产生一种短的无功能蛋白质。缺乏全长产物产生疾病的症状。理解DNA突变指导截短蛋白质制造的方式需要对翻译的终止阶段以及核糖体对遗传信息突变的反应方式有基本的了解。过程的复杂性要求开发新的工具来研究支撑该过程的生物化学。一套这样的工具，数学和计算建模，可以用来生成翻译和终止步骤的定量描述。一旦模型化，翻译可以使用计算机模拟进行研究，与实验室实验研究平行。生物化学过程的建模是一个新兴的领域，为理解细胞控制电路的复杂性提供了令人兴奋的前景。在这项提案中，生物学家将与控制/系统工程师合作，对翻译过程进行建模，包括终止步骤。由于酵母和人类细胞中的终止过程相似，因此将研究模式生物面包酵母的终止过程。此外，存在一系列突出翻译终止步骤的反馈控制的酵母突变体。对这些突变体以及反馈环如何被控制的研究，为研究控制蛋白质合成和调节细胞中所有蛋白质长度的许多参数提供了一个令人兴奋的机会。从长远来看，这种理解可以应用于囊性纤维化等人类遗传疾病影响的研究。