Temperature-Dependent Model of Multi-step Transcription Initiation in Escherichia coli Based on Live Single-Cell Measurements

• Published in: PLoS computational biology Vol. 12; no. 10; p. e1005174
• Main Authors: Oliveira, Samuel M D, Häkkinen, Antti, Lloyd-Price, Jason, Tran, Huy, Kandavalli, Vinodh, Ribeiro, Andre S
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.10.2016; Public Library of Science (PLoS)
• Subjects: Biology and life sciences; Colleges & universities; Computer Simulation; E coli; Escherichia coli; Escherichia coli - physiology; Escherichia coli Proteins - metabolism; Funding; Gene expression; Genetic aspects; Genetic transcription; Laboratories; Medicine and Health Sciences; Models, Biological; Models, Statistical; Monte Carlo simulation; Observations; Physical Sciences; Promoter Regions, Genetic - physiology; Research and Analysis Methods; Signal processing; Standard deviation; Temperature; Transcription Initiation Site - physiology; Transcription, Genetic - physiology; Transcriptional Activation - physiology
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1005174

Transcription kinetics is limited by its initiation steps, which differ between promoters and with intra- and extracellular conditions. Regulation of these steps allows tuning both the rate and stochasticity of RNA production. We used time-lapse, single-RNA microscopy measurements in live Escherichia coli to study how the rate-limiting steps in initiation of the Plac/ara-1 promoter change with temperature and induction scheme. For this, we compared detailed stochastic models fit to the empirical data in maximum likelihood sense using statistical methods. Using this analysis, we found that temperature affects the rate limiting steps unequally, as nonlinear changes in the closed complex formation suffice to explain the differences in transcription dynamics between conditions. Meanwhile, a similar analysis of the PtetA promoter revealed that it has a different rate limiting step configuration, with temperature regulating different steps. Finally, we used the derived models to explore a possible cause for why the identified steps are preferred as the main cause for behavior modifications with temperature: we find that transcription dynamics is either insensitive or responds reciprocally to changes in the other steps. Our results suggests that different promoters employ different rate limiting step patterns that control not only their rate and variability, but also their sensitivity to environmental changes.