In-Sequence Coding of Stochastic Gene Expression Via Synonymous Mutations

Harvard University, Cambridge MA

Investigators

Abstract

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.