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Modeling and Engineering Promoters with Pre-defined RNA Production Dynamics in Escherichia Coli

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationComputational Methods in Systems Biology - 16th International Conference, CMSB 2018, Proceedings
PublisherSpringer Verlag
Pages3-20
Number of pages18
ISBN (Print)9783319994284
DOIs
Publication statusPublished - 2018
Publication typeA4 Article in a conference publication
EventInternational Conference on Computational Methods in Systems Biology - Brno, Czech Republic
Duration: 12 Sep 201814 Sep 2018

Publication series

NameLecture Notes in Bioinformatics
Volume11095 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Computational Methods in Systems Biology
CountryCzech Republic
CityBrno
Period12/09/1814/09/18

Abstract

Recent developments in live-cell time-lapse microscopy and signal processing methods for single-cell, single-RNA detection now allow characterizing the in vivo dynamics of RNA production of Escherichia coli promoters at the single event level. This dynamics is mostly controlled at the promoter region, which can be engineered with single nucleotide precision. Based on these developments, we propose a new strategy to engineer genes with predefined transcription dynamics (mean and standard deviation of the distribution of RNA numbers of a cell population). For this, we use stochastic modelling followed by genetic engineering, to design synthetic promoters whose rate-limiting steps kinetics allow achieving a desired RNA production kinetics. We present an example where, from a pre-defined kinetics, a stochastic model is first designed, from which a promoter is selected based on its rate-limiting steps kinetics. Next, we engineer mutant promoters and select the one that best fits the intended distribution of RNA numbers in a cell population. As the modelling strategies and databases of models, genetic constructs, and information on these constructs kinetics improve, we expect our strategy to be able to accommodate a wide variety of pre-defined RNA production kinetics.

Keywords

  • Gene engineering framework, Model of transcription initiation, Rate-limiting steps, Synthetic constructs

Publication forum classification

Field of science, Statistics Finland