Evaluating codon optimization strategies for mammalian glycoprotein production with an open-source expression vector

Abstract

Efficient production of human proteins for the development of tool compounds and biologics depends on a detailed understanding of the protein expression machinery in mammalian cells. Codon optimization is widely believed to enhance protein yield, yet its impact in homologous mammalian systems remains poorly defined. Here, we systematically compare five codon usage strategies reflecting common assumptions about rare codons, RNA stability, and synthesis efficiency. We developed pTipi, an efficient open-source mammalian expression vector, and evaluated its performance in antibody production. We generated plasmids for common epitope tag antibodies such as V5, anti-biotin and anti-His for distribution by Addgene. To compare codon usage schemes, we performed a bake-off of 18 human and murine Wnt pathway glycoproteins in mammalian cells. Small-scale expression screens revealed that codon optimization did not provide a general advantage over native coding sequences, while strategies prioritizing RNA stability consistently reduced expression. Interestingly, a skewed codon scheme using the most abundant codons produced yields comparable to native sequences and occasionally enhanced protein output. To enable flexible evaluation of codon strategies, we implemented a Golden Gate-compatible pTipi platform for efficient synthetic gene incorporation. We conclude that native codons are sufficient for robust homologous mammalian expression of glycoproteins, while selective codon skewing can be beneficial for some targets.