Cue-driven microbial cooperation and communication: evolving quorum sensing with honest signaling

Area of Science:

• Microbiology
• Evolutionary Biology
• Computational Biology

Background:

• Quorum sensing (QS) enables microorganisms to gauge population density via signaling molecules, coordinating group behaviors.
• Cooperation via QS is vulnerable to 'laggards' and 'liars' who exploit the system.
• The prevalence of QS-supported cooperation despite these vulnerabilities requires explanation.

Purpose of the Study:

• Investigate the evolutionary stability of cue-based quorum sensing (QS) in microbial cooperation.
• Analyze how inevitable QS signal byproducts (cues) affect cooperation dynamics.
• Determine the conditions under which cue-driven cooperation is evolutionarily advantageous.

Main Methods:

• Spatially explicit agent-based lattice simulations were employed.
• Three analytical and numerical approximations of the lattice model were used.
• The models explored QS-aided threshold cooperation under various parameter values.

Main Results:

• Cue-driven cooperation prevents 'laggards' from undermining cooperative efforts, especially at high thresholds.
• 'Lying' (cheating with fake signals) is strongly selected against when signals are inevitable byproducts.
• QS is most effective when local cooperator densities are unpredictable and near the cooperation threshold.

Conclusions:

• Cue-driven threshold cooperation is a viable evolutionary strategy in both viscous and well-mixed microbial environments.
• This model resembles the 'greenbeard' effect, maintaining stable coexistence of cooperators and defectors.
• Condition-dependent trade-offs in signal production, characteristic of cue-based QS, maintain this evolutionary polymorphism.