Models of protein production along the cell cycle: An investigation of possible sources of noise.

Renaud Dessalles,Philippe Robert,Vincent Fromion,Jordi Garcia-Ojalvo

doi:10.1371/journal.pone.0226016

Abstract

In this article, we quantitatively study, through stochastic models, the effects of several intracellular phenomena, such as cell volume growth, cell division, gene replication as well as fluctuations of available RNA polymerases and ribosomes. These phenomena are indeed rarely considered in classic models of protein production and no relative quantitative comparison among them has been performed. The parameters for a large and representative class of proteins are determined using experimental measures. The main important and surprising conclusion of our study is to show that despite the significant fluctuations of free RNA polymerases and free ribosomes, they bring little variability to protein production contrary to what has been previously proposed in the literature. After verifying the robustness of this quite counter-intuitive result, we discuss its possible origin from a theoretical view, and interpret it as the result of a mean-field effect.

Highlights

For some time fluorescent microscopy methods have provided quantitative measurements of gene expression on the level of individual cells, see for instance [1, 2]
In the Materials and Methods section, we describe in detail our approach that considers models that integrates the features that are missing in the two-stage model previously described
The mRNA number seems to have the most important effect on protein production: for the same average protein concentration, having more mRNAs greatly diminish protein variance; such effect has been experimentally observed [2, 35]. This can be interpreted as lower bursting effect in protein production: as it is known that mRNAs in few copies with large activity display a protein production with large bursts, a large number of mRNAs less active leads to a more stable protein production

Summary

Introduction

Fluorescent microscopy methods have provided quantitative measurements of gene expression on the level of individual cells, see for instance [1, 2]. Measurements have shown that protein production is a highly variable process, even for genetically identical cells in constant environmental conditions. The fluctuations can negatively affect genetic expression and impact the behavior of the cell (see [3]), or, on the contrary, beneficially participate in strategies to adapt to a changing environment [4, 5]. [6] performed an extensive quantification of the variability of the gene expression of around a thousand different genes in E. coli. For a significant number of the genes considered, messenger RNA production is quantified in each cell: using an mRNAsequencing technique (RNA-seq), they were able to estimate the average production of 841

Objectives

Methods

Results

Conclusion