In-Sequence Coding of Stochastic Gene Expression Via Synonymous Mutations

由于20种氨基酸中的18种在DNA水平上由多个同义密码子编码，因此蛋白质合成过程中使用的遗传密码是高度冗余的——密码子是编码氨基酸的三个DNA碱基对的序列。虽然众所周知，蛋白质可以由不同的同义密码子编码，但这种冗余密码子对蛋白质合成效率的作用仍不清楚。值得注意的是，研究者发现在营养匮乏的情况下，同义密码子在合成水平和不同细胞合成蛋白质数量的变化中都扮演着非常不同的角色。发现一些密码子对某些氨基酸的限制具有鲁棒性，从而允许更强的蛋白质表达，而其他密码子对这种限制敏感，从而产生低水平的蛋白质表达。重要的是，细胞被认为在细菌生物膜的形成过程中或在癌细胞增殖过程中挨饿，同义密码子应该在调节蛋白质合成中发挥重要作用。因此，本项目的目标是量化和确定同义密码子在营养饥饿期间蛋白质合成中的作用。培养具有数学或生物学科学背景的学生是这一努力的重要组成部分。学生将有机会亲身参与从本项目提供的数据中提取基因表达的动态模拟。在过去的十年中，物理学家和生物学家对开发一个定量框架来预测单细胞水平上基因表达的随机行为非常感兴趣。在细菌中，已经出现了一个清晰的图景：基因表达中的噪音主要是由泊松分布的转录爆发引起的，而翻译本身放大了这些波动。当细菌在富培养基中生长时，这个经典模型成立，但它无法解释当细菌暴露于环境扰动（如营养限制）时观察到的噪音。这个项目的结果将是创建一个新的物理框架来预测在环境扰动下由敏感同义密码子的顺序分布所控制的基因表达中的噪声。在这里，研究者提出表征与稳健和敏感密码子相关的噪声，当用于编码黄色荧光蛋白的表达。首先，研究者将专注于量化由同义密码子选择引起的随机细胞间基因表达行为。其次，将进行工作来确定与同义词敏感密码子翻译相关的动力学如何表现出接近临界的行为。最后，第三个目的是研究在特征良好的环境扰动下，由同义密码子驱动的关键细胞内参数变化作为噪声控制参数的贡献。该奖项由物理部的生命系统物理学项目和分子和细胞生物科学部的细胞动力学和功能项目共同支持。

Because 18 of the 20 amino acids are encoded at the DNA level with multiple synonymous codons, the genetic code used during protein synthesis is highly redundant -- a codon is the sequence of three DNA base pairs coding an amino acid. While it is well known that proteins can be encoded by different synonymous codons, the role of this redundant code on the efficiency of protein synthesis has remained unclear. Remarkably, the investigator found that under nutrient starvation, synonymous codons played very distinct roles on both synthesis levels and the variations from one cell to another of the quantity of synthetized proteins. Some codons were found to be robust to the limitation of certain amino acids, allowing for stronger protein expression, while others were sensitive to this limitation yielding low levels of protein expression. Importantly, cells are believed to starve during the formation of bacterial biofilms or during cancerous proliferation for which synonymous codons should play an important role in regulating protein synthesis. Therefore, the goal of this project is to quantify and establish the role of synonymous codons in protein synthesis during starvation of nutrients. The training of students with scientific backgrounds in mathematics or biology is an important component of this effort. Students will have the opportunity for hands-on participation in dynamics simulation of gene expression extracted from data made possible by this project. Over the last decade, there has been considerable interest from physicists and biologists to develop a quantitative framework to predict the stochastic behavior of gene expression at the single cell level. In bacteria, a clear picture has emerged: noise in gene expression is mainly caused by transcriptional bursts that are Poisson distributed and translation solely amplifies these fluctuations. While this canonical model holds when bacteria grow in rich media, it fails to explain the observed noise when bacteria are exposed to environmental perturbations such as nutrient limitation. The outcome of this project will be to create a novel physical framework to predict the noise in gene expression governed by the in-sequence distribution of sensitive synonymous codons under environmental perturbations. Here the investigator proposes to characterize the noise associated with robust and sensitive codons when used to encode the expression of the yellow fluorescent protein. Firstly, the investigator will focus on quantifying the stochastic cell-to-cell behavior in gene expression arising from synonymous codon choice. Secondly, work will be done to identify how the dynamics associated with the translation of synonymous sensitive codons exhibits near-critical behavior. Finally, the third aim examines the contribution of the variations of key intracellular parameters as control parameters of noise driven by synonymous codons under well-characterized environmental perturbations.This award is supported jointly by the Physics of Living Systems Program in the Physics Division and the Cellular Dynamics and Function Program in the Division of Molecular and Cellular Biosciences.