Transcription dynamics of inducible genes modulated by negative regulations.

Gene transcription is a stochastic process in single cells, in which genes transit randomly between active and inactive states. Transcription of many inducible genes is also tightly regulated: It is often stimulated by extracellular signals, activated through signal transduction pathways and later repressed by negative regulations. In this work, we study the nonlinear dynamics of the mean transcription level of inducible genes modulated by the interplay of the intrinsic transcriptional randomness and the repression by negative regulations. In our model, we integrate negative regulations into gene activation process, and make the conventional assumption on the production and degradation of transcripts. We show that, whether or not the basal transcription is temporarily terminated when cells are stimulated, the mean transcription level grows in the typical up and down pattern commonly observed in immune response genes. With the help of numerical simulations, we clarify the delicate impact of the system parameters on the transcription dynamics, and demonstrate how our model generates the distinct temporal gene-induction patterns in mouse fibroblasts discerned in recent experiments.