Autor(es): Martins, Leonardo Pedro Donas-Boto de Vilhena
Data: 2011
Identificador Persistente: http://hdl.handle.net/10362/7009
Origem: Repositório Institucional da UNL
Assunto(s): Stochastic simulation; Transcription initiation; Prokaryotic gene expression; Rregulation mechanisms; Promoter arrangements
Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
The regulatory mechanisms of transcription allow organisms to quickly adapt to changes in their environment and often act during transcription initiation. Here, a stochastic model of transcription initiation at the nucleotide level is proposed to study the dynamics of RNA production in closely spaced promoters and their regulatory mechanisms. We study how different arrangements (convergent e divergent), distance between transcription start sites (TSS), and various kinetic parameters affect the dynamics of RNA production. Further, we analyze how the kinetics of various steps in transcription initiation can be regulated by varying locations of repressor binding sites. From the results, we observe that the rate limiting steps have strong influence in the kinetics of RNA production. We find that interferences between RNA polymerases in divergent overlapped and convergent geometries causes the distribution of time intervals between the production of consecutive RNA molecules from each TSS to increase in mean and standard deviation, which leads to stronger fluctuations in the temporal levels of RNA molecules. We observe that small changes in the distance between TSSs can lead to abrupt transitions in the dynamics of RNA production, particularly when this change changes the geometry from overlapped to non-overlapped promoters. From the study of the correlation in the choices of directionality and on the time series of RNA productions we show that by tuning the distances and directions of the two TSS one can obtain both negative and positive correlations. We further show that distinct repression mechanisms of transcription initiation in steps such as the open and closed complex formation and promoter escape have different effects on the dynamics of RNA production. The study of these models will help the study of how genetic circuits have evolved and assist in designing artificial genetic circuits with desired dynamics.
