(654d) Engineering the Secretion and Surface Display of Heterologous Proteins in Y. Lipolytica

Proteins are integral to the pharmaceutical industry, playing a crucial role in the development of therapeutic agents, vaccines, and diagnostic tools. The demand for protein-based pharmaceuticals, like monoclonal antibodies and enzymes, has grown exponentially. In 2022, the U.S. Recombinant Protein Manufacturing market was a $3.5 billion industry, and is expected to increase by almost 20% by 2030. However, cost-effective production of these proteins remains a significant challenge. One of the primary contributors to the high cost of protein production is the extensive downstream processing required to reach product purity standards, which often involves cell lysis, multiple filtration steps, and chromatography. There is an inverse relationship between the amount of product present in the fermentation broth and the cost of production, meaning that the more protein is secreted, the more cost effective the process becomes. My work involves upstream engineering of a yeast cell line to decrease the need for expensive downstream purification. The GRAS (generally regarded as safe) yeast Yarrowia lipolytica was chosen for this work due to its well understood genome, native ability to perform post-translational modifications, and its superior ability to secrete proteins compared to S. cerevisiae. The aim of this work is to further improve the secretion capabilities of Y. lipolytica through genetic editing.

A common strategy in protein secretion optimization involves incorporating a heterologous secretion signal into the protein's coding sequence, but identifying the most effective signal is challenging due to the unpredictability of which signal will work best for a specific protein. To address this issue, this work uses a CRISPR knockout library to identify genes whose knockout improves protein secretion in yeast.

A high-throughput assay is required when doing CRISPR library work since the scale is often millions of cells. However, measuring the changes in secretion of individual cells is very difficult in a bulk culture. To overcome this challenge, we are using surface display as a proxy for secretion since there is a direct relationship between the amount of protein secreted and the amount of protein surface displayed because all surface proteins must travel through the secretory pathway. The platform we have developed displays an anti-GFP nanobody on the surface of Y. lipolytica that, when treated with GFP, has fluorescence that can be analyzed using flow cytometry. The CRISPR-(knockout) KO library will be transformed into the surface display strain of Y. lipolytica and the top 5% of fluorescing cells will be collected, which will then be analyzed to determine what gene knockouts are responsible for the increase in surface display of anti-GFP nanobody. To determine if these improvements are universal, these knockouts will then be applied to a strain of Y. lipolytica that produces and secretes the protein α-amylase, a protein that degrades starch.

By utilizing a CRISPR knockout library and surface display technology, this work aims to identify key genes that enhance protein secretion, thus reducing the need for costly downstream processing. The future goal of this work is to measure the changes in secretion made by the CRISPR-KO library directly using microdroplet technology which involves encapsulating single cells in small droplets where their secretion can be measured directly. These droplets would then be sorted via flow assisted cell sorting (FACS), after which the droplets would be dissolved and the cells analyzed for gene knockouts.