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Quantitative modeling of the function of kinetically driven transcriptional riboswitches.

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Riboswitches are cis-acting regulatory mRNA elements in bacteria, that modulate the expression of their associated genes in response to a cognate metabolite, operating either on the level of translation or… Click to show full abstract

Riboswitches are cis-acting regulatory mRNA elements in bacteria, that modulate the expression of their associated genes in response to a cognate metabolite, operating either on the level of translation or transcription. Transcriptional riboswitches have to fold into functional structures as they are being synthesized and, only if transcription rates and ligand binding kinetics match, structured transcription intermediates are enabled to undergo ligand-dependent conformational refolding as a prerequisite for ligand-mediated gene expression. Therefore, transcription rates are of essential importance for functional riboswitch-mediated gene regulation. Here, we propose a generalized modeling framework for the kinetic mechanisms of transcriptional riboswitches. The formalism accommodates time-dependent transcription rates and changes of metabolite concentration and permits incorporation of variations in transcription rate depending on transcript length. We derive explicit analytical expressions for the fraction of transcripts that determine repression or activation of gene expression as a function of pause site location and its slowing down of transcription for the case of the (2'dG)-sensing riboswitch from Mesoplasma florum. Our modeling challenges the current view on the exclusive importance of metabolite binding to transcripts containing only the aptamer domain. Numerical simulations of transcription proceeding in a continuous manner under time-dependent changes of metabolite concentration further suggest that rapid modulations in concentration result in a reduced dynamic range for riboswitch function regardless of transcription rate, while a combination of slow modulations and small transcription rates ensures a wide range of finely tuneable regulatory outcomes.

Keywords: transcription; transcriptional riboswitches; quantitative modeling; transcription rates; modeling function

Journal Title: Journal of theoretical biology
Year Published: 2020

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