Bilateral NSF/BIO-BBSRC: Synthetic gene circuits to measure and mitigate translational stress during heterologous protein expression

在这个项目中，一个由生物学家和物理学家组成的跨学科团队将建立新的技术，以提高细胞以更高的效率和更高的精度制造重组蛋白质(RP)的能力。生物技术行业的大部分致力于生产用作药品、疫苗和食品添加剂的RPS。这些蛋白质是在活细胞中使用正常的蛋白质合成过程制造的，而这些相同蛋白质的工业化生产需要异常高的蛋白质水平--以至于所需的蛋白质占细胞中所有蛋白质质量的大部分。在如此高的产量水平，当错误的氨基酸被插入到不断增长的蛋白质链中时，蛋白质就会被错误地制造出来。该项目将研究这些错误是如何积累的，并将创建基因电路，可以感知蛋白质合成错误频率的任何显著增加，并可以部署机制来恢复正常的高精度蛋白质合成。研究团队由巴尔的摩县马里兰大学的实验室和英国阿伯丁大学的实验室组成，前者研究的是一种模型细菌E.Coli，后者的研究对象是面包师的酵母。这两个团队还将与英国的一家大型生物技术公司合作，以确保该项目的产品将直接用于工业规模的蛋白质生产。蛋白质中的氨基酸由信使核糖核酸中的三个核苷酸密码子编码；翻译涉及信使核糖核酸密码子和tRNA反密码子之间的三个核苷酸碱基对。当解码tRNA只与密码子形成两个碱基对时，就会出现错误。对于每个正确的(同源的)tRNA，大约有14个不正确的(近同源的)tRNA可能导致这样的错误。解码过程通常非常准确，接近同源的tRNA引入错误氨基酸的频率从大约10,000到1,000,000之一。错译也可能由移码引起，即选择与正确密码子重叠的密码子进行解码。在翻译由低丰度tRNA提供服务的密码子时，或在带电tRNA耗尽引起的核糖体停顿期间，这些误译错误的频率急剧增加。生物技术蛋白质的高水平表达正是创造了这些条件，从而增加了翻译错误的频率。事实上，许多报告描述了生物技术蛋白质的表达产生了一系列不受欢迎的误翻译事件，损害了产品的产量和质量，从而影响了生物制品的安全性和有效性。在这个项目中，我们将通过设计和应用能够产生报告酶活性或调节转录因子的新型误翻译报告器来更好地理解翻译错误的系统范围的原因。我们将这些实验方法与翻译和tRNA竞争的全球数学模型相结合，以预测系统压力何时会刺激误翻译。然后，我们使用合成生物基因电路来转录连接这些新的错误翻译传感器的输出，以控制RP的表达，减少错误翻译，提高RP产品质量。我们的工业合作伙伴将测试这些合成基因电路，以最大限度地扩大机会，实现这项研究对生物技术的影响。这项研究将首次揭示RPS在触发翻译系统压力中的作用，并找出缓解压力的新方法。

In this project, an interdisciplinary team of biologists and physicists will establish novel technologies to improve the ability of a cell to make recombinant proteins (rPs) at higher efficiency and with greater accuracy. A majority of the biotechnology industry is dedicated to the production of rPs for use as pharmaceuticals, vaccines and food additives. These proteins are made in living cells using the normal process of protein synthesis, whereas the industrial production of these same proteins requires unusually high levels of the protein - such that the desired protein accounts for the majority of all protein mass in the cell. At such a high production level, proteins are made with errors, when incorrect amino acids are inserted into the growing protein chain. This project will investigate how these errors accumulate, and will create genetic circuits that can sense any significant increase in the frequency of protein synthesis errors and can deploy mechanisms to restore normal highly accurate protein synthesis. The research team consists of the lab at University of Maryland Baltimore County, working with a model bacterium E.coli, and the lab at the University of Aberdeen, UK, working with baker`s yeast. The two teams will also collaborate with a major biotechnology company in the United Kingdom to insure that the products of the project will be directly applicable to use in industrial scale protein production.Amino acids in proteins are encoded by three nucleotide codons in mRNA; translation involves three nucleotide base pairs between the mRNA codon and a tRNA anticodon. Errors occur when a decoding tRNA forms only two base pairs with the codon. For each correct (cognate) tRNA there are about fourteen incorrect (near-cognate) tRNAs that could induce such an error. The decoding process is normally highly accurate, with near-cognate tRNAs introducing incorrect amino acids at frequencies from about one in 10,000 to as low as one in 1,000,000. Mistranslation can also result from frameshifting in which a codon overlapping the correct codon is selected for decoding. The frequency of these mistranslation errors increase sharply during translation of codons served by low abundance tRNA, or during ribosomal pausing caused by depletion of charged tRNAs. The high-level expression of biotechnological proteins can creates exactly these conditions and thus increasing translational error frequencies. Indeed, many reports describe biotechnological protein expression generating a range of undesirable mistranslation events, compromising product yield and quality, and thus the safety and efficacy of biologics. In this project we will pursue a better understanding of the system-wide causes of translational error through the design and application of novel reporters of mistranslation, capable of producing either reporter enzyme activities, or regulatory transcription factors. We combine these experimental approaches with global mathematical modelling of translation and tRNA competition to predict when system stress will stimulate mistranslation. We then use synthetic biology gene circuits to transcriptionally couple the output from these new mistranslation sensors to control rP expression, to reduce mistranslation and increase rP product quality. Our industrial partner will test these synthetic gene circuits to maximize the opportunities for realizing the impact of this research on biotechnology. This research will reveal for the first time the role of rPs in triggering translation system stress, and identify novel ways in which stress can be ameliorated.