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

Feiran Li; Yu Chen; Qi Qi; Yanyan Wang; Le Yuan; Mingtao Huang; Ibrahim El-Semman; Amir Feizi; Eduard Kerkhoven; Jens B Nielsen

doi:10.1038/s41467-022-30689-7

Improving recombinant protein production by yeast through genome-scale modeling using proteome constraints
Journal article, 2022

Eukaryotic cells are used as cell factories to produce and secrete multitudes of recombinant pharmaceutical proteins, including several of the current top-selling drugs. Due to the essential role and complexity of the secretory pathway, improvement for recombinant protein production through metabolic engineering has traditionally been relatively ad-hoc; and a more systematic approach is required to generate novel design principles. Here, we present the proteome-constrained genome-scale protein secretory model of yeast Saccharomyces cerevisiae (pcSecYeast), which enables us to simulate and explain phenotypes caused by limited secretory capacity. We further apply the pcSecYeast model to predict overexpression targets for the production of several recombinant proteins. We experimentally validate many of the predicted targets for alpha-amylase production to demonstrate pcSecYeast application as a computational tool in guiding yeast engineering and improving recombinant protein production. Due to the complexity of the protein secretory pathway, strategy suitable for the production of a certain recombination protein cannot be generalized. Here, the authors construct a proteome-constrained genome-scale protein secretory model for yeast and show its application in the production of different misfolded or recombinant proteins.