Modeling slow-processing of toxin messenger RNAs in type-I toxin-antitoxin systems: post-segregational killing and noise filtering

Preventing toxicity in toxin-antitoxin systems: An overview of regulatory mechanisms

Toxin-antitoxin systems (TAs) are generally two-component genetic modules present in almost every prokaryotic genome. The production of the free and active toxin is able to disrupt key cellular processes leading to the growth inhibition or death of its host organism in absence of its cognate antitoxin. The functions attributed to TAs rely on this lethal phenotype ranging from mobile genetic elements stabilization to phage defense. Their abundance in prokaryotic genomes as well as their lethal potential make them attractive targets for new antibacterial strategies. The hijacking of TAs requires a deep understanding of their regulation to be able to design such approach. In this review, we summarize the accumulated knowledge on how bacteria cope with these toxic genes in their genome. The characterized TAs can be grouped based on the way they prevent toxicity. Some systems rely on a tight control of the expression to prevent the production of the toxin while others control the activity of the toxin at the post-translational level.

A minimal model for gene expression dynamics of bacterial type II toxin-antitoxin systems

Toxin-antitoxin (TA) modules are part of most bacteria's regulatory machinery for stress responses and general aspects of their physiology. Due to the interplay of a long-lived toxin with a short-lived antitoxin, TA modules have also become systems of interest for mathematical modelling. Here we resort to previous modelling efforts and extract from these a minimal model of type II TA system dynamics on a timescale of hours, which can be used to describe time courses derived from gene expression data of TA pairs. We show that this model provides a good quantitative description of TA dynamics for the 11 TA pairs under investigation here, while simpler models do not. Our study brings together aspects of Biophysics with its focus on mathematical modelling and Computational Systems Biology with its focus on the quantitative interpretation of 'omics' data. This mechanistic model serves as a generic transformation of time course information into kinetic parameters. The resulting parameter vector can, in turn, be mechanistically interpreted. We expect that TA pairs with similar mechanisms are characterized by similar vectors of kinetic parameters, allowing us to hypothesize on the mode of action for TA pairs still under discussion.

Excitable dynamics through toxin-induced mRNA cleavage in bacteria

Toxin-antitoxin (TA) systems in bacteria and archaea are small genetic elements consisting of the genes coding for an intracellular toxin and an antitoxin that can neutralize this toxin. In various cases, the toxins cleave the mRNA. In this theoretical work we use deterministic and stochastic modeling to explain how toxin-induced cleavage of mRNA in TA systems can lead to excitability, allowing large transient spikes in toxin levels to be triggered. By using a simplified network where secondary complex formation and transcriptional regulation are not included, we show that a two-dimensional, deterministic model captures the origin of such toxin excitations. Moreover, it allows to increase our understanding by examining the dynamics in the phase plane. By systematically comparing the deterministic results with Gillespie simulations we demonstrate that even though the real TA system is intrinsically stochastic, toxin excitations can be accurately described deterministically. A bifurcation analysis of the system shows that the excitable behavior is due to a nearby Hopf bifurcation in the parameter space, where the system becomes oscillatory. The influence of stress is modeled by varying the degradation rate of the antitoxin and the translation rate of the toxin. We find that stress increases the frequency of toxin excitations. The inclusion of secondary complex formation and transcriptional regulation does not fundamentally change the mechanism of toxin excitations. Finally, we show that including growth rate suppression and translational inhibition can lead to longer excitations, and even cause excitations in cases when the system would otherwise be non-excitable. To conclude, the deterministic model used in this work provides a simple and intuitive explanation of toxin excitations in TA systems.