Analysis of Translation Elongation Dynamics in the Context of an Escherichia coli Cell

Understanding the mechanisms behind translation and its rate-limiting steps is crucial for both the development of drug targets and improvement of heterologous protein production with many biotechnological applications, such as in pharmaceutical and biofuel industries. Despite many advances in the knowledge of the ribosome structure and function, there is still much discussion around the determinants of translation elongation with experiments and computational studies pointing in different directions. Here, we use a stochastic framework to simulate the process of translation in the context of an Escherichia coli cell by gathering the available biochemical data into a ribosome kinetics description. Our results from the study of translation in E. coli at different growth rates contradict the increase of mean elongation rate with growth rate established in the literature. We show that both the level of tRNA competition and the type of cognate binding interaction contribute to the modulation of elongation rate, and that optimization of a heterologous transcript for faster elongation rate is achieved by combining the two. We derive an equation that can accurately predict codon elongation rates based on the abundances of free tRNA in the cell, and can be used to assist transcript design. Finally, we show that non-cognate tRNA-ribosome binding has an important weight in translation, and plays an active role in the modulation of mean elongation rate as shown by our amino-acid starvation/surplus studies.

Vassily Hatzimanikatis, Joana Raquel Pinto Vieira, Julien Racle

Elsevier2016

A computational framework for the design of optimal protein synthesis

Vassily Hatzimanikatis, Jan Overney, Julien Racle

Despite the establishment of design principles to optimize codon choice for heterologous expression vector design, the relationship between codon sequence and final protein yield remains poorly understood. In this work, we present a computational framework for the identification of a set of mutant codon sequences for optimized heterologous protein production, which uses a codon-sequence mechanistic model of protein synthesis. Through a sensitivity analysis on the optimal steady state configuration of protein synthesis we are able to identify the set of codons, that are the most rate limiting with respect to steady state protein synthesis rate, and we replace them with synonymous codons recognized by charged tRNAs more efficient for translation, so that the resulting codon-elongation rate is higher. Repeating this procedure, we iteratively optimize the codon sequence for higher protein synthesis rate taking into account multiple constraints of various types. We determine a small set of optimized synonymous codon sequences that are very close to each other in sequence space, but they have an impact on properties such as ribosomal utilization or secondary structure. This limited number of sequences can then be offered for further experimental study. Overall, the proposed method is very valuable in understanding the effects of the different properties of mRNA sequences on the final protein yield in heterologous protein production and it can find applications in synthetic biology and biotechnology.

Wiley-Blackwell2012

Deciphering translation - a genome-wide analysis of translation in Escherichia coli

Vassily Hatzimanikatis, Julien Racle

Protein synthesis is one of the central elements in every living cell. For this process, mRNAs coding for genes are simultaneously competing for the same translation machinery (ribosomes and amino acids). But the ultimate determinants of cellular functions are the proteins, a good understanding of this process is therefore of crucial importance. For this purpose, we developed a genome-wide, mechanistic, mathematical model of translation, taking into account individual codon kinetics. It is used to quantify the rate limiting steps of translation and gain insight into the mechanism of regulation of expression between different proteins. We observe for each gene in a first low-occupancy phase a nearly linear increase in protein synthesis rate with amount of bound ribosomes to the mRNA, followed by a plateau of maximum synthesis rate. A further increase in the ribosomal coverage of the mRNA leads to a decrease in protein production rate, and might act as sinks for system resources like ribosomes. Native E. coli gene sequences are also compared to randomly obtained synonymous sequences, coding the same protein, and it is found some genes of higher significance for the cell have been better optimized for protein synthesis rate than other.

2010