Modeling Quorum Sensing Dynamics and Interference on Escherichia coli.

Area of Science:

• Microbiology
• Systems Biology
• Mathematical Biology

Background:

• Bacteria utilize Quorum Sensing (QS) for gene regulation via signaling molecules called Autoinducers (AIs).
• Autoinducer-2 (AI-2) is a key AI involved in interspecies bacterial communication.
• Understanding AI-2 dynamics is crucial for controlling bacterial behavior.

Purpose of the Study:

• To develop and validate a mathematical model of AI-2 dynamics in *Escherichia coli*.
• To investigate the relationship between AI-2 activity, cell growth rate, and *lsr* operon expression.
• To simulate QS interference strategies in co-cultures of *E. coli* strains.

Main Methods:

• Development of a mathematical model for AI-2 dynamics linked to *E. coli* growth and *lsr* operon.
• Model calibration using experimental data.
• Simulation of co-culture scenarios involving wild-type and AI-2 non-producing *E. coli* strains.

Main Results:

• Extracellular AI-2 activity is dependent on the cell growth rate, particularly during the exponential growth phase.
• The model successfully simulated interference with QS in co-cultures.
• Two conditions were identified to inhibit QS in wild-type *E. coli*: competitive exclusion by a knockout strain or pre-culturing the knockout strain.

Conclusions:

• Bacterial AI-2 dynamics are intrinsically linked to cellular growth phases.
• Mathematical modeling provides insights into bacterial communication interference.
• The study offers potential tools for controlling QS mechanisms in bacterial populations.