[Application of codon optimization strategy in heterologous protein expression]

Area of Science:

• Biotechnology and Biopharmaceuticals
• Molecular Biology
• Enzyme Engineering

Background:

• Enzymes are crucial in medicine and biopharmaceuticals for disease treatment and diagnosis.
• Microbial expression is the primary method for obtaining enzymes, necessitating high-quality heterologous protein production.
• Traditional codon optimization focuses on codon bias and GC content, neglecting crucial factors like translational dynamics and metabolic states.

Purpose of the Study:

• To develop a comprehensive codon optimization strategy for enhanced heterologous protein expression.
• To integrate gene, transcriptional, translational, post-translational, and metabolic levels into optimization.
• To provide a multi-faceted approach for improving enzyme production in biopharmaceutical applications.

Main Methods:

• Developed a multi-level codon optimization strategy considering gene, transcriptional, translational, post-translational, and metabolic factors.
• Incorporated codon bias, codon harmonization, codon sensitivity, and gene sequence structure adjustments.
• Systematically compared the advantages and disadvantages of various optimization strategies.

Main Results:

• The proposed strategy offers a more holistic approach to codon optimization compared to traditional methods.
• Identified key factors influencing heterologous protein expression beyond simple codon bias.
• Demonstrated a multi-selection optimization framework for diverse enzyme production needs.

Conclusions:

• The comprehensive strategy enhances heterologous protein expression for enzyme production in biopharmaceuticals.
• This approach provides a valuable reference for the enzyme and biopharmaceutical industries.
• Offers an all-round, multi-level optimization solution for efficient enzyme manufacturing.