Bistability and oscillations in co-repressive synthetic microbial consortia

Area of Science:

• Synthetic biology
• Microbial ecology
• Computational modeling

Background:

• Synthetic microbial consortia utilize engineered microbes for cooperative population-level phenotypes.
• Intercellular signaling pathways enable coordinated gene transcription regulation within consortia.
• Emergent behaviors in microbial consortia are challenging to engineer into single-strain populations.

Purpose of the Study:

• To computationally model the behavior of synthetic microbial consortia.
• To investigate the interplay between population dynamics and intercellular signaling.
• To understand how regulatory topologies and strain interactions influence consortium stability.

Main Methods:

• Computational modeling of synthetic microbial consortia dynamics.
• Analysis of a two-strain consortium with co-repressive signaling.
• Examination of population dynamics, transcriptional regulation, and growth rate feedback.

Main Results:

• Consortium state stability depends on population-level dynamics and relative strain fractions.
• Fluctuations in strain fractions can drive the consortium to alternative equilibria.
• Strain-specific growth rate dependencies on transcriptional states can lead to relaxation oscillations.

Conclusions:

• Microbial consortium dynamics are not solely determined by regulatory topology.
• Interactions between strains significantly influence consortium behavior and stability.
• Computational modeling is crucial for predicting emergent behaviors in synthetic microbial consortia.