Hierarchical Post-transcriptional Regulation of Colicin E2 Expression in Escherichia coli

Abstract

Post-transcriptional regulation of gene expression plays a crucial role in many bacterial pathways. In particular, the translation of mRNA can be regulated by trans-acting, small, non-coding RNAs (sRNAs) or mRNA-binding proteins, each of which has been successfully treated theoretically using two-component models. An important system that includes a combination of these modes of post-transcriptional regulation is the Colicin E2 system. DNA damage, by triggering the SOS response, leads to the heterogeneous expression of the Colicin E2 operon including the cea gene encoding the toxin colicin E2, and the cel gene that codes for the induction of cell lysis and release of colicin. Although previous studies have uncovered the system’s basic regulatory interactions, its dynamical behavior is still unknown. Here, we develop a simple, yet comprehensive, mathematical model of the colicin E2 regulatory network, and study its dynamics. Its post-transcriptional regulation can be reduced to three hierarchically ordered components: the mRNA including the cel gene, the mRNA-binding protein CsrA, and an effective sRNA that regulates CsrA. We demonstrate that the stationary state of this system exhibits a pronounced threshold in the abundance of free mRNA. As post-transcriptional regulation is known to be noisy, we performed a detailed stochastic analysis, and found fluctuations to be largest at production rates close to the threshold. The magnitude of fluctuations can be tuned by the rate of production of the sRNA. To study the dynamics in response to an SOS signal, we incorporated the LexA-RecA SOS response network into our model. We found that CsrA regulation filtered out short-lived activation peaks and caused a delay in lysis gene expression for prolonged SOS signals, which is also seen in experiments. Moreover, we showed that a stochastic SOS signal creates a broad lysis time distribution. Our model thus theoretically describes Colicin E2 expression dynamics in detail and reveals the importance of the specific regulatory components for the timing of toxin release.

Eco-evolutionary dynamics of a population with randomly switching carrying capacity

“…The DMN models suddenly changing conditions, reflecting several situations in bacterial life, such as cells living at either side of a physical phase transition [1], or in the ever-changing conditions of a host digestive tract. In the laboratory, bacteria can be subjected to complex gut-like environment [54] or simplified stressful conditions, typically through variable exposure to antibiotics [55][56][57]. Furthermore, with modern bioengineering techniques it is possible to perform controled microbial experiments in settings allowing for sensible comparisons with theoretical models sharing some of the features considered here (switching environment, time-varying population size, public good production) [16,17,30,36].…”

The Evolution of Mass Cell Suicide in Bacterial Warfare

“…This construct, like others previously studied [10,12,22,23], allows one to identify cells that may be on their way to cell suicide via lysis [1–3]. However, it is not sufficient to follow the full behaviour, as the self-lysis process is dependent on the expression of the lysis gene in the colicin operon [18,24], which is subject to several additional layers of regulation at both the transcriptional and post-transcriptional level [17,25–28]. Moreover, with this reporter alone, it is impossible to tell if a cell that died was killed by external toxins while building up colicins or if it had undergone self-lysis.…”

CsrA and its regulators control the time-point of ColicinE2 release in Escherichia coli

“…To elucidate the role of CsrA theoretically, we extended our previous mathematical model as described in 28 (Methods). To show that our model is indeed valid, we employed parameters motivated by experimental studies (please see SI for details) to reproduce the delay distribution of the S REP1 strain (Fig.…”