Modeling classic attenuation regulation of gene expression in bacteria.

A model is proposed primarily for the classical RNA attenuation regulation of gene expression through premature transcription termination. The model is based on the concept of the RNA secondary structure macrostate within the regulatory region between the ribosome and RNA-polymerase, on hypothetical equation describing deceleration of RNA-polymerase by a macrostate and on views of transcription and translation initiation and elongation, under different values of the four basic model parameters which were varied. A special effort was made to select adequate model parameters. We first discuss kinetics of RNA folding and define the concept of the macrostate as a specific parentheses structure used to construct a conventional set of hairpins. The originally developed software that realizes the proposed model offers functionality to fully model RNA secondary folding kinetics. Its performance is compared to that of a public server described in Ref. 1. We then describe the delay in RNA-polymerase shifting to the next base or its premature termination caused by an RNA secondary structure or, herefrom, a macrostate. In this description, essential concepts are the basic and excited states of the polymerase first introduced in Ref. 2: the polymerase shifting to the next base can occur only in the basic state, and its detachment from DNA strand - only in excited state. As to the authors' knowledge, such a model incorporating the above-mentioned attenuation characteristics is not published elsewhere. The model was implemented in an application with command line interface for running in batch mode in Windows and Linux environments, as well as a public web server.(3) The model was tested with a conventional Monte Carlo procedure. In these simulations, the estimate of correlation between the premature transcription termination probability p and concentration c of charged amino acyl-tRNA was obtained as function p(c) for many regulatory regions in many bacterial genomes, as well as for local mutations in these regions.