First Passage Time statistics in cell trajectories

In cellular environment the underlying noise is crucial for gene expression driving the system to a state that is difficult to predict a priori. Noise interferes also with the timing of cellular processes that is crucial, for example for cellular response to an external signal. For this reason it is important to understand if there is some process that regulates the stochastisticity of processes timing. In particular timing is crucial in several cellular processes that rely on precise temporal organisation. This happens in cell-cycle control, cell differentiation, development, temporal order of gene expression where regulatory proteins must reach some critical threshold level. During cell development there is a set of sequentially ordered biochemical processes for which is required a tight control of expression timing. In particular the idea is to calculate the First Passage Time in gene expression that is the time at which, during a protein genesis process, the protein expression reaches a treshold. Other studies have been done in the case in which no regulation was present giving important result since the noise is minimized for certain value of the threshold, in particular half for the protein mean value at the steady state. The work aims to find, if there are, differencies in results by adding the miRNA regulation in the models already tested. To do so has been implemented a Gillespie algorithm that simulate the protein genesis machinery in presence of a miRNA regulation. Experimental data were also produced by transfetting in the cellular enviroment to produce two different proteins with a bidirectional promoter that produces two fluorescent proteins, one of which is regulated by miRNA. The two proteins dynamics has been measured and collected in order to calculate a FPT also in a real system.