Improving recombinant protein production by yeast through genome-scale modeling using proteome constraints

Area of Science:

• Biotechnology
• Systems Biology
• Metabolic Engineering

Background:

• Eukaryotic cells, particularly yeast Saccharomyces cerevisiae, are vital cell factories for producing recombinant pharmaceutical proteins.
• The secretory pathway's complexity necessitates systematic approaches for metabolic engineering to optimize protein production.
• Current methods for improving recombinant protein production are often ad-hoc, highlighting the need for novel design principles.

Purpose of the Study:

• To develop a proteome-constrained genome-scale protein secretory model for yeast (pcSecYeast).
• To simulate and elucidate phenotypes associated with limited secretory capacity in yeast.
• To identify and predict overexpression targets for enhanced recombinant protein production.

Main Methods:

• Development of the proteome-constrained genome-scale protein secretory model (pcSecYeast) for Saccharomyces cerevisiae.
• Simulation of yeast phenotypes related to secretory pathway limitations.
• Application of the model to predict gene overexpression targets for recombinant protein production.

Main Results:

• The pcSecYeast model successfully simulates and explains phenotypes arising from limited secretory capacity.
• The model predicted several overexpression targets for enhancing recombinant protein production.
• Experimental validation confirmed many predicted targets for α-amylase production.

Conclusions:

• The pcSecYeast model serves as a valuable computational tool for guiding yeast engineering.
• This systematic approach significantly improves the efficiency of recombinant protein production in yeast.
• The developed model offers a foundation for designing novel strategies in biopharmaceutical manufacturing.