Cooperative and sequence-dependent model for RNAP dynamics: Application to ribosomal gene transcription.

Escherichia coli ribosomal genes are a well-established experimental model used to investigate the transcription process. These genes are essential to cell physiology and are therefore strongly expressed. Multiple transcription units collaborate in rrn expression. Experiments involving electron microscopy have shown the non-uniform density of the RNA polymerases transcribing these ribosomal operons. Here, we investigate RNAP collaborative transcription in E. coli ribosomal genes using a stochastic sequence-dependent model that included interactions among the RNAPs. We achieved results consistent with experimental data using a model with variable parametrization for genic and intergenic regions, compared with previous attempts that used uniform parameters for genic and intergenic regions. Our model also showed that cooperative behaviour reduced the dwell times in pause sites predicted by the single-round approach but induced a new pausing event at an upstream position. This work may stimulate new experimental research and provide other scenarios to test our model predictions.

Cooperative RNA polymerase molecules behavior on a stochastic sequence-dependent model for transcription elongation.

The transcription process is crucial to life and the enzyme RNA polymerase (RNAP) is the major component of the transcription machinery. The development of single-molecule techniques, such as magnetic and optical tweezers, atomic-force microscopy and single-molecule fluorescence, increased our understanding of the transcription process and complements traditional biochemical studies. Based on these studies, theoretical models have been proposed to explain and predict the kinetics of the RNAP during the polymerization, highlighting the results achieved by models based on the thermodynamic stability of the transcription elongation complex. However, experiments showed that if more than one RNAP initiates from the same promoter, the transcription behavior slightly changes and new phenomenona are observed. We proposed and implemented a theoretical model that considers collisions between RNAPs and predicts their cooperative behavior during multi-round transcription generalizing the Bai et al. stochastic sequence-dependent model. In our approach, collisions between elongating enzymes modify their transcription rate values. We performed the simulations in Mathematica® and compared the results of the single and the multiple-molecule transcription with experimental results and other theoretical models. Our multi-round approach can recover several expected behaviors, showing that the transcription process for the studied sequences can be accelerated up to 48% when collisions are allowed: the dwell times on pause sites are reduced as well as the distance that the RNAPs backtracked from backtracking sites.