Collaborative Research: Data-driven engineering of the yeast Kluyveromyces marxianus for enhanced protein secretion

University Of California-Riverside, Riverside CA

Investigators

Abstract

Purification is the limiting step in protein production. If the protein can be secreted out of the cell, purification is much easier and simpler. Certain yeasts are proficient at protein secretion. The objective of this project is to develop a yeast strain with a robust protein secretion system that is also tolerant to extreme pH and temperature levels. Gene editing tools such as CRISPR will enable the improvement of a native yeast. Production of a broad range of proteins will be evaluated. This project also focuses on improving STEM education for underrepresented minorities and non-traditional students at the high school, community college, and undergraduate levels. Improving success in college and the diversity of the US biotechnology workforce are desired outcomes. The secretory pathway of the yeast Kluyveromyces marxianus will be engineered. Genome-wide CRISPR-Cas9 knockout, CRISPRi, and CRISPRa libraries will be used to identify critical genes influencing protein production and secretion. These screens should generate large datasets that link phenotype-to-genotype. This data will be used to inform a second phase of the project. In the second phase, multiplexed CRISPR-based gene-regulation will identify synergistic combinations leading to more efficient protein secretion. The research could result in effective CRISPR gRNA libraries, optimized selection strategies, fundamental knowledge of the secretory pathway in this emerging industrial yeast, and a library of gene interventions leading to substantially higher protein secretion for a range of proteins. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.