Noise Minimization in Gene Expression Switches

GUTIERREZ, P.S.; MONTEOLIVA, D.; DIAMBRA, L.

Barcelona

Encuentro; Computational approaches to networks, cells and tissues; 2013

QuanTissue

Gene expression is subject to stochastic variation that lead to fluctuations in the rate of protein production. These fluctuations arise because of the small copy number of species undergoing transitions between discrete chemical states and the small size of biological compartments. In the last years, the noise expression level associated to single genes has been quantified in prokaryote and eukaryote organisms. More recently, it has also been quantified in yeast at the genomic scale. In this case, it has been shown that the expression variability of some genes alters phenotypes, while they are robust against the fluctuations in the expression of other genes. These studies suggest that noise in gene expression is a physiologically relevant trait, and it is subject to be minimized to prevent harmful stochastic variation in the expression levels of some genes. However, the mechanisms for noise minimization is still unclear. In the present work, we present a model for stochastic gene expression that includes several regulatory sites. Using this model, we found that the fluctuation level in noise expression decreases with the number of regulatory sites when the unbound transcription factor interacts with only one bound transcription factor. In contrast, we observe that there is an optimal number of binding sites when transcription factors interact with many regulatory sites. This finding suggests a new mechanism to prevent large fluctuation in the expression of genes which are sensitive to the concentration of regulators.