Resolving emergent transient oscillations in gene circuits with a growth-coupled model

Area of Science:

• Synthetic Biology
• Computational Biology
• Biophysics

Background:

• Synthetic gene circuits often exhibit unpredictable dynamics in batch cultures.
• Conventional models typically do not account for shifting cellular physiological states during growth.

Purpose of the Study:

• To develop a multiscale modeling framework that accurately predicts synthetic gene circuit behavior across different growth stages.
• To resolve discrepancies between standard models and observed transient oscillatory expression in degradation-tagged protein reporters.

Main Methods:

• Developed Gene Expression Across Growth Stages (GEAGS), a dual-scale modeling framework.
• Coupled intracellular gene expression with logistic population growth using a chemical reaction network.
• Incorporated growth phase-dependent rate-modifying functions.

Main Results:

• GEAGS accurately reproduced observed transient oscillatory expression patterns.
• Identified amino acid recycling and growth-phase transition as key drivers of oscillations.
• Demonstrated model adaptability by applying it to layered feedback circuits, resolving prediction mismatches.

Conclusions:

• GEAGS provides a generalizable platform for predicting emergent behaviors in synthetic gene circuits.
• Highlights the critical importance of multiscale modeling for robust synthetic circuit design in dynamic environments.