Classical stochastic modelsof protein production usually do not consider several phenomena within the cell such as cell volume growth, cell division or gene replication , furthermore concentrations of RNA-polymerases and ribosomesare in general assumed to be constant. In this paper we study the effects induced by all these different aspects on protein variability. Starting from the classical two-stage protein production model, we successively integrate the volume growth, the random partition of compounds at division, the gene replication and the sharing of RNA-polymerases and ribosomes for the production of all types of proteins. Experimental measures are used to determine the numerical values of the parameters of our models. We are then able to investigate the impact of these different phenomena on the variability of a large class of proteins  . The main conclusions are that, among all different mechanisms studied, the random partitioning of macro-molecules at division is the only one which may have a significant impact on the variance of protein concentration. In particular, the variability induced by the sharing of RNA-polymerases and ribosomes seems to be of a smaller order of magnitude than what is generally suggested in the literature  .
In this article, we quantitatively study, through stochastic models, the efects of several intracellular phenomena, such as cell volume growth, cell division , gene replication as well as fuctuations 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 signifcant fuctuations 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-feld efect .
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Classical stochastic modelsof protein production usually do not consider several phenomena within the cell
In this article, we quantitatively study, through stochastic models, the efects of several intracellular phenomena,
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or gene replication , furthermore concentrations of RNA-polymerases and ribosomesare in general assumed to be constant. In this paper we study the effects induced by all these different aspects on protein variability. Starting from the classical two-stage protein production model, we successively integrate the volume growth, the random partition of compounds at division, the gene replication and the sharing of RNA-polymerases and ribosomes for the production of all types of proteins. Experimental measures are used to determine the numerical values of the parameters of our models. We are then able to investigate the impact of these different phenomena on the variability of a large
, gene replication as well as fuctuations 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
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are determined using experimental measures
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conclusions are that, among all different mechanisms studied, the random partitioning of macro-molecules at division is the only one which may have a significant impact on the variance of protein concentration. In particular, the variability induced by the sharing of RNA-polymerases and ribosomes seems to be of a smaller order of magnitude than what is generally suggested
important and surprising conclusion of our study is to show that despite the signifcant fuctuations of free RNA polymerases and free ribosomes, they bring little variability to protein production contrary to what has been previously proposed
A
. 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-feld efect