Competition for intracellular resources: from experimental data to parameter estimation.

In recent years, modeling genetic circuits has emerged as a powerful tool to unravel underlying mechanisms of gene expression. Experimental data of single cells expressing two fluorescent proteins (mCherry and eYFP) over time are available and present various shapes and behaviours which are not predictable by standard models of gene regulation assuming infinite resources. Inspired by many studies suggesting that competition for molecular resources can modify and shape the response of a genetic circuit, this Master's Thesis aims to understand if a resource-aware model can be used to correctly predict gene expression in environments with finite pools of intracellular resources. To do this, a minimal stochastic model is built to study the simple case where only the ribosomes are present in finite number, investigate the effects of this finite pool on gene expression levels, and infer model parameters. In order to fix as many parameters as possible, we performed wet-lab experiments with HEK293 Tet-off cells transfected with plasmids containing sequences for mCherry and eYFP fluorescent proteins. Degradation rates of the proteins are then estimated using fluorescence microscopy, while the degradation rates of mRNAs are estimated via quantitative PCR techniques. Experimental data of the two fluorescent proteins are used to infer other parameters that are difficult to determine experimentally.