High-throughput metabolic engineering of <i>Yarrowia lipolytica</i> through gene expression tuning
Wei Jiang, Shengbao Wang, Daniel Ahlheit, T. Fumagalli, Zhijie Yang, Sridhar Ramanathan, Xinglin Jiang, Tilmann Weber, Jonathan Dahlin, Irina Borodina
Abstract
The challenge of accurately predicting which genetic alternations lead to the desired phenotype necessitates high-throughput metabolic engineering approaches where numerous hypotheses can be tested simultaneously. We describe the CRISPR-Cas9-based method TUNE YALI that enables high-throughput tuning of gene expression in the common industrial yeast Yarrowia lipolytica . The method is based on replacing the promoters of the target genes with native Y. lipolytica promoters of varying strengths or removing the promoters entirely. To demonstrate the method’s capabilities, we created a plasmid library that targets 56 transcription factors (TFs) and changes the expression of each TF to seven different levels. We transformed this library into reference and betanin-producing strains of Y. lipolytica and screened the resulting clones for changes in morphology, thermotolerance, or improved betanin production. The genetic markup of the yeast clones with the desired phenotypic changes was determined by sequencing the inserted plasmids. We identified multiple TFs whose regulatory changes increased thermotolerance, two TFs that eliminated pseudohyphal growth, and several TFs that increased betanin production. Analogous libraries can be designed to target any chosen group of genes and even all the genes. The libraries can be shared and reused, accelerating applied strain development projects and fundamental functional genomics research (TUNE YALI -TF kit and TUNE YALI -TF library are available via AddGene under catalog numbers #1000000255 and #217744).