Cooperative RNA Polymerase Molecules Behavior on a Stochastic Sequence-Dependent Model for Transcription Elongation

Autor(es)

Costa, Pedro Rafael ^[1] ; Acencio, Marcio Luis ^[1] ; Lemke, Ney ^[1]

Afiliação do(s) autor(es)

^[1] UNESP Univ Estadual Paulista, Inst Biociencias Botucatu, Dept Fis & Biofis, Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: PLoS One; v. 8, n. 2 FEB 21 2013.
• Citações Web of Science: 5

Resumo

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 (R) 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. (AU)

• Processo FAPESP: 09/10382-2 - Aprendizado de máquina em biologia molecular de sistemas
• Beneficiário: Ney Lemke
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 10/20684-3 - Utilização de aprendizado de máquina em redes biológicas para previsão e determinação de regras para emergência de fenótipos de interesse
• Beneficiário: Marcio Luis Acencio
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 10/03338-4 - Modelo cinético estocástico para a transcrição em eucariotos considerando colisões entre moléculas de RNA Pplimerase II
• Beneficiário: Pedro Rafael Costa
• Modalidade de apoio: Bolsas no Brasil - Mestrado