A selectable system to evaluate synthetic gene optimization features

Abstract

Heterologous gene expression – transferring genes from a natural cell or origin to another host cell, often across species – is a fundamental technique in biological research as well as biotechnological and pharmaceutical manufacturing. Optimization of gene sequences, therefore, is a critical factor when enhanced protein yield is needed. For any given protein, an enormous diversity of nucleotide sequences comprising the vast combinatorics of possible codon combinations could theoretically be used to encode the same amino acid sequence. The process of “codon optimization” typically replaces certain codons thought to be suboptimal with a more optimal codon encoding the same amino acid. However, such methods cannot address the enormity of possible nucleotide sequences possible to encode a given protein, or to decipher potential factors in addition to codon usage that may affect gene expression. Here we utilize the Sh ble gene encoding zeocin resistance in a system comprising bioinformatic synthetic gene production and an antibiotic selection platform. We find that supposedly codon optimized genes do not produce enhanced antibiotic resistance, suggesting that other factors are more important in synthetic gene optimization and heterologous gene expression.