Controlling protein expression by using intron-aided promoters in Saccharomyces cerevisiae

Pathway flux imbalance is a challenge in metabolic engineering, which may be overcome by tuning expression level of the involved proteins. A library of promoters with a wider range of strengths can be used to search a larger combinatorial search space and identify stronger genetic parts to improve protein expression level. In this study, we developed new tools for better controlling gene expression in Saccharomyces cerevisiae. The tools are based on introns, which mediate pre-mRNA splicing. By combining nine promoters with eight introns, a library of 72 intron-aided promoters was created. Screening this library revealed that the introns can improve the dynamic range (strength of the strongest promoter over that of the weakest one) of the promoter library (from 2.4- to 7-fold). A predictive model was trained based on this set of data and was subsequently used to evaluate 260 S. cerevisiae native introns in silico, which were ranked according to their capacity of improving a commonly used promoter, PTEF1. Three top-ranked candidates substantially improved PTEF1 strength in the experimental validations. The intron-promoter library and the model developed in this study should be a useful addition to the tool sets of engineering S. cerevisiae, an important microbial workhorse used in production of value-added chemicals.