Journal Article

The route to transcription initiation determines the mode of transcriptional bursting in E. coli

Engl, Christoph, Jovanovic, Goran, Buck, Martin, Kotta-Loizou, Ioly, Brackston, Rowan D.

2020

Overview

Transcription is fundamentally noisy, leading to significant heterogeneity across bacterial populations. Noise is often attributed to burstiness, but the underlying mechanisms and their dependence on the mode of promotor regulation remain unclear. Here, we measure E. coli single cell mRNA levels for two stress responses that depend on bacterial sigma factors with different mode of transcription initiation (σ 70 and σ 54 ). By fitting a stochastic model to the observed mRNA distributions, we show that the transition from low to high expression of the σ 70 -controlled stress response is regulated via the burst size, while that of the σ 54 -controlled stress response is regulated via the burst frequency. Therefore, transcription initiation involving σ 54 differs from other bacterial systems, and yields bursting kinetics characteristic of eukaryotic systems. Transcription noise in bacteria is often attributed to burstiness, but the mechanisms are unclear. Here, the authors show that the transition from low to high expression can be regulated via burst size or burst frequency, depending on the mode of transcription initiation determined by different sigma factors.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 14/32 / 38/71 / 631/326/325/2482 / 631/337/572 / Adenosine Triphosphate - chemistry / Bacteria / Bayes Theorem / Burst size / Bursting / DNA-Directed RNA Polymerases - metabolism / E coli / Escherichia coli - genetics / Escherichia coli Proteins - metabolism / Gene Expression Regulation, Bacterial / Heterogeneity / Humanities and Social Sciences / Hydrolysis / Kinetics / Models, Genetic / multidisciplinary / Promoter Regions, Genetic / RNA Polymerase Sigma 54 - metabolism / RNA, Messenger - metabolism / Route selection / Science / Science (multidisciplinary) / Sigma Factor - metabolism / Single-Cell Analysis / Stochastic models / Stochastic Processes / Transcription initiation / Transcription, Genetic