Noise in Gene Expression: Cooperativity and Synergy

GUTIERREZ, P.S.; DIAMBRA, L.

Buenos Aires

Congreso; Giambiagi winter school; 2013

UBA

Eukaryotic gene expression, at transcriptional level, is mainly controlled by the cis-regulatory system (CRS) which cover the core promoter elements and transcription factors regulatory binding sites on DNA. Transcription factors (TF) bind specifically to regulatory sites and interact with components of basal transcriptional machinery (BTM) facilitating or hindering assembly of functional pre-initiation complex (PIC) on the core promoter elements. Transcriptional initiation is a tightly controlled process that includes several timed steps. But TF bind to the regulatory sites and form the PIC in a stochastic fashion, turning the transition between states of CRS into stochastic process. As the number of TF molecules and the number of regulatory binding sites are too small, the deterministic assumptions, though valid in the limit of a macroscopic system, fail to describe these mesoscopic systems. Therefore, instead of a smooth deterministic course, the fundamentally random nature of chemical reactions results in noisy reaction trajectories in individual cells. Thus, in the last decade a stochastic approach has been taken into account when the gene expression has been studied. Regardless to the potential diversity of the CRS architecture and functionality when one considers the many known components and regulatory mechanisms in PIC formation, most of the stochastic models for gene expression regulatory studies proposed are based on transitions between two CRS states (active and inactive). Despite their simplicity, these models are able to extract valuable information about the gene expression fluctuations. For example, they have illustrated that fast chemical kinetics are responsible for a graded response, whereas slow kinetics lead to a binary response. Nevertheless, simple models may not be suitable to study the role of different mechanisms participating in complex transcriptional regulation processes. Here we proposed a mathematical model, at transcriptional level of gene expression regulation, which considers a CRS with several regulatory binding sites for a single activating TF (Figure 1). By means of the master equation approach we derived analytical expressions for the first two moments of the steady-state probability distribution for transcripts (mRNA), i.e. the mean transcriptional levels and associated fluctuations, and studied three different cooperative mechanisms: cooperative TF-DNA binding, cooperative TF-BTM binding and cooperative BTM activation.