Codon-tRNA Coadaptation Bias for Identifying Strong Native Promoters in Komagataella phaffii.

Abstract

Promoters are crucial elements for engineering microbial production strains used in bioprocesses. For the increasingly popular chassis Komagataella phaffii (formerly Pichia pastoris), a limited number of well-characterized promoters constrain the data-driven engineering of production strains. Here, we present an in silico approach for condition-independent de novo identification of strong native promoters. The method relies on tRNA-codon coadaptation of coding sequences in the K. phaffii genome and is based on two complementary scores: the number of effective codons and the tRNA adaptation index. Genes with high codon bias are expected to be translated efficiently and, thus, also be under control of strong promoters. Using this approach, we identified promising strong promoter candidates and experimentally assessed their activity using fluorescent reporter assays characterizing 50 promoters spanning a 76-fold difference in expression levels in a glucose medium. Overall, we report several promoters that should be added to the molecular toolbox for engineering of K. phaffii and present an approach for identifying promoters in microbial genomes.