Ribosome traffic flow on the mRNA as a regulator of cellular protein production: an integrated modelling and experimental analysis

在这项提案中，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来预测细胞的蛋白质组成。所有生物体内的细胞都利用蛋白质来进行构成生命的基本生化过程。知道一个细胞制造了哪些蛋白质和蛋白质的数量，就定义了这个特定细胞的特性。因此，能够预测细胞的蛋白质组成是了解细胞生物学的一个非常有力的工具。蛋白质本身是由一串被称为氨基酸的化学构件组成的，其中有20种不同的类型。正是蛋白质链中氨基酸的独特序列赋予了蛋白质的生化和催化特性。即使是一个相对简单的有机体，比如面包酵母，也可以有大约6000种不同种类的蛋白质，每一种都有自己特定的氨基酸序列。细胞利用基因中编码的信息制造出正确氨基酸序列的蛋白质。每个基因编码一种蛋白质，所以面包酵母有6000个基因编码相同数量的不同蛋白质。为了制造蛋白质，基因中的编码信息首先被复制到一种称为信使RNA （mRNA）的短线性分子中。然后被称为核糖体的生物分子组合读取mRNA中的信息，这一过程被称为翻译。核糖体沿着mRNA从一端移动到另一端，读取mRNA中编码的信息，并通过顺序添加氨基酸来翻译它，从而形成蛋白质链。氨基酸通过转移RNA分子（trna）进入核糖体。然后，这种蛋白质被释放出来，在细胞中发挥它的功能。事实上，mRNA可以同时被多个核糖体翻译，核糖体就像道路上的汽车一样相互跟随。这个交通类比相当贴切；有时，就像汽车在交通堵塞中卡住一样，核糖体在翻译mRNA时也会减慢速度，甚至完全停止，通常是对mRNA中难以翻译的部分做出反应。当这种情况发生时，核糖体的队列就会形成，从而降低蛋白质产生的速度。所有mrna都由许多不同的慢速和快速翻译区域组成，例如，由不同tRNA物种的不同丰度引起。然后核糖体队列可以开始合并，有时会延伸到mRNA的开头，阻止核糖体加入mRNA。这将减少由mRNA引导的蛋白质合成量。因此，mrna上的核糖体流量是制造不同蛋白质数量的关键调节器。因此，要了解细胞将表达哪一种蛋白质以及表达的数量，就需要能够预测mRNA上的核糖体流量，以及整个核糖体群体如何与酵母中6000种mRNA中的每一种相互作用。准确预测核糖体在翻译过程中如何相互作用和排队是一项具有挑战性的任务，需要数学和生物学技术的联合应用。在提出这一建议的工作中，我们开发了一个数学模型来模拟mrna上的核糖体流量。该模型对核糖体流量如何影响mrna的翻译做出了许多重要的预测，这些预测将在本提案中进行测试。拟议的研究还将进一步发展该模型，纳入翻译过程的详细数学描述。该模型将通过酵母翻译反应的实验分析进行验证。总的来说，跨学科的方法不仅将提供对细胞用于表达其基因的基本机制的真正见解，而且将对生物学和物理学中许多其他交通流系统的研究产生影响。

In this proposal, an interdisciplinary team of biologists and physicists will establish novel technologies to predict the protein composition of a cell. Proteins are used by the cells within all organisms to carry out the essential biochemical processes that constitute life. Knowing which proteins and in what quantities are being made by a cell, defines the properties of that particular cell. Being able to predict the protein composition of a cell therefore represents a very powerful tool to understand cell biology. Proteins themselves are made of a string of chemical building blocks called amino acids, of which there are twenty different types. It is the distinct sequence of the amino acids in the protein chain that gives the protein its biochemical and catalytic properties. Even a relatively simple organism such as baker's yeast, the subject of this proposal, can have about 6,000 different varieties of protein, each with its own specific amino acid sequence. The cell makes proteins of the correct amino acid sequence using information encoded in its genes. Each gene codes for a single protein type, so baker's yeast has 6,000 genes encoding the same number of distinct proteins. To make a protein, the coding information in a gene is first copied into a short linear molecule termed a messenger RNA, or mRNA. Then an assembly of bio-molecules called ribosome reads the information within the mRNA, a process called translation. The ribosome moves along the mRNA from one end to the other, reading the information coded in the mRNA, and translating it by sequentially adding the amino acids to make a protein chain. The amino acids are brought to the ribosomes by transfer RNA molecules (tRNAs). The protein is then released to carry out its function in the cell. In fact, the mRNA can by translated by multiple ribosomes at the same time, with ribosomes following each other like cars down a road. This traffic analogy is rather apt; sometimes, just as cars get stuck in a traffic jam, so ribosomes can slow down or even pause completely as they translate the mRNA, usually in response to a section of the mRNA that is difficult to translate. When this happens, queues of ribosomes can build up, reducing the rate at which that protein is produced. All mRNAs are comprised of many different slowly and rapidly translated regions, for instance, caused by different abundances of distinct tRNA species. Ribosome queues can then begin to merge, sometimes extending back to the beginning of the mRNA and preventing ribosomes from joining the mRNA. This will reduce the amount of protein synthesis directed by that mRNA. Ribosomal traffic flow on mRNAs is therefore a key regulator of the quantities of the different proteins being made. To understand which population of proteins a cell will express, and in which quantities, therefore requires an ability to predict ribosomal traffic flow on the mRNA, and how whole populations of ribosomes interact with each of the 6,000 mRNAs in yeast. Predicting exactly how ribosomes interact and queue as they translate is a challenging task that requires joint application of both mathematical and biological techniques. In work leading up to this proposal, we have developed a mathematical model to simulate ribosome traffic on mRNAs. This model makes a number of important predictions about how ribosome traffic flow affects the translation of mRNAs, predictions that will be tested in this proposal. The proposed research will also develop the model much further, incorporating detailed mathematical descriptions of the translation process. The model will be tested and validated by experimentally analysing translation reactions in yeast. Overall, the interdisciplinary approach will not only provide genuine insight into the fundamental mechanisms a cell uses to express its genes, but will have implications for the study of many other traffic flow systems in Biology and Physics.