Cooperative RNA Polymerase Molecules Behavior on a Stochastic Sequence-Dependent Model for Transcription Elongation - Costa, Pedro Rafael [UNESP]; Acencio, Marcio Luis [UNESP]; Lemke, Ney [UNESP] (Public Library of Science (PLoS), 2013)
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. © 2013 Costa et al.
Keywords: RNA polymerase; catalysis; DNA strand; DNA template; enzyme active site; enzyme modification; molecular dynamics; prediction; protein interaction; reaction time; RNA transcription; stochastic model; transcription elongation; Algorithms; Bacteriophage T7; Computer Simulation; DNA-Directed RNA Polymerases; Models, Genetic; Monte Carlo Method; Stochastic Processes; Thermodynamics; Transcription Elongation, Genetic; Viral Proteins