Genome-wide screen for enhanced noncanonical amino acid incorporation in yeast

Abstract

Numerous applications of noncanonical amino acids (ncAAs) in basic biology and therapeutic development require efficient protein biosynthesis using an expanded genetic code. However, achieving such incorporation at repurposed stop codons in cells is generally inefficient and limited by complex cellular processes that preserve the fidelity of protein synthesis. A more comprehensive understanding of the processes that contribute to ncAA incorporation would aid in the development of genomic engineering strategies for augmenting genetic code manipulation. In this work, we screened a pooled Saccharomyces cerevisiae molecular barcoded yeast knockout (YKO) collection to identify single-gene knockout strains exhibiting improved ncAA incorporation efficiency in response to the amber (TAG) stop codon. We used a series of intracellular fluorescent reporters in tandem with fluorescence activated cell sorting (FACS) to identify 55 unique candidate deletion strains. Identified genes encode for proteins that participate in diverse cellular processes; many of the genes have no known connection with protein translation. We then verified that two knockouts, yil014c-aΔ and alo1Δ, had improved incorporation efficiency using independently acquired strains possessing the knockouts. Characterizations of the activity of yil014c-aΔ and alo1Δ with additional orthogonal translation systems and ncAAs indicate that deletion of each of these genes enhances ncAA incorporation efficiency without loss of fidelity over a wide range of conditions. Our findings highlight opportunities for further modulating gene expression with genetic, genomic, and synthetic biology approaches to improve ncAA incorporation efficiency. In addition, these discoveries have the potential to enhance our fundamental understanding of protein translation. Ultimately, this study provides a foundation for future efforts to engineer cells to incorporate ncAA at greater efficiencies, which in turn will streamline the realization of applications utilizing expanded genetic codes ranging from basic biology to drug discovery.