Modeling and measuring how codon usage modulates the relationship between burden and yield during protein...

Area of Science:

• Synthetic Biology
• Molecular Biology
• Biophysics

Background:

• Cellular burden from over-expressing exogenous proteins impacts yields and stability.
• Codon optimization is used to enhance translational efficiency but its quantitative impact on cellular burden is unclear.

Purpose of the Study:

• To develop and evaluate a stochastic gene expression model quantifying the relationship between codon usage bias and cellular burden.
• To investigate how codon optimization affects ribosome and tRNA availability and impacts native protein production.

Main Methods:

• Developed a stochastic gene expression model incorporating codon usage bias, ribosome, and tRNA availability.
• Experimentally tested the model by expressing sfGFP and mCherry2 at various codon optimization levels in Escherichia coli.

Main Results:

• Exogenous protein expression linearly decreases native protein production, with the slope modulated by codon usage match.
• A codon overoptimization domain was identified where increased optimal codon usage worsens yield and burden.
• Experimental results in E. coli validated model predictions, including negative effects of overoptimization.

Conclusions:

• Codon optimization strategies need to be nuanced, considering potential negative impacts of overoptimization.
• The developed model provides a framework for predicting and designing improved cellular systems for protein expression.