Optimisation of gene expression noise for cellular persistence against lethal events

Area of Science:

• Microbiology and Systems Biology
• Investigating the fundamental mechanisms of bacterial survival and adaptation.

Background:

• Bacterial cell persistence is vital for surviving antibiotic stress.
• Stochastic gene expression fluctuations influence antibiotic tolerance.
• Specific genes can confer antibiotic tolerance at higher expression levels.

Purpose of the Study:

• To determine optimal protein expression strategies for bacterial survival under antibiotic pressure.
• To mathematically model the relationship between gene expression, cell growth, and survival probability.
• To analyze how the cost of protein expression impacts optimal survival strategies.

Main Methods:

• Mathematical modeling and analysis of bacterial gene expression dynamics.
• Simulation of cellular responses to antibiotic events.
• Investigation of burst size and frequency effects on cell proliferation.
• Exploration of the influence of growth costs on optimal expression distributions.

Main Results:

• Identified optimal burst size and frequency for maximizing cell proliferation.
• Demonstrated how the optimal expression distribution shifts with increasing growth costs.
• Revealed a hysteresis phenomenon with discontinuous transitions between deterministic and stochastic optima.
• Established the existence of a 'noise floor' for optimal cellular resilience.

Conclusions:

• Optimal bacterial survival during antibiotic exposure is achieved through a balance of gene expression and stochasticity.
• A minimal level of gene expression noise (noise floor) is essential for maximal cellular resilience.
• Understanding these dynamics can inform strategies to combat antibiotic resistance.