Excitable dynamics through toxin-induced mRNA cleavage in bacteria.

Area of Science:

• Microbiology
• Biophysics
• Computational Biology

Background:

• Toxin-antitoxin (TA) systems are genetic elements in bacteria and archaea.
• These systems comprise a toxin and an antitoxin that neutralizes it.
• Toxins often function by cleaving mRNA.

Purpose of the Study:

• To theoretically explain excitability in TA systems using mathematical modeling.
• To investigate how toxin-induced mRNA cleavage triggers large transient spikes in toxin levels.
• To understand the underlying mechanisms of toxin excitations.

Main Methods:

• Utilized deterministic and stochastic modeling approaches.
• Employed a simplified two-dimensional deterministic model to analyze toxin excitations.
• Performed bifurcation analysis and compared deterministic results with Gillespie simulations.
• Modeled the influence of stress by varying antitoxin degradation and toxin translation rates.

Main Results:

• A simplified deterministic model accurately captures toxin excitations in TA systems.
• Excitable behavior arises from a nearby Hopf bifurcation, leading to oscillations.
• Increased stress (altered degradation/translation rates) enhances the frequency of toxin excitations.
• Complex network features like secondary complex formation and transcriptional regulation do not alter the core excitation mechanism.

Conclusions:

• Deterministic modeling provides a simple and intuitive explanation for toxin excitations in TA systems.
• The study demonstrates that stochastic bacterial systems can be accurately described by deterministic models for toxin excitations.
• Stress significantly influences the frequency of toxin excitations, with potential implications for bacterial physiology.