PhD Research

Genetic Engineering Yeast.

Since the summer of 2020, I have been working in the Ian Wheeldon lab at UC Riverside. From producing cannabinoids in yeast to designing “smart yeast” with molecular sensors, the general theme of my projects seek to genetically engineer yeast to produce novel chemicals and develop new genetic engineering tools.

Production of Cannabinoids in Yarrowia lipolytica

Cannabinoids are powerful biomolecules from the Cannabis sativa plant. Even forgetting about the psychoactive THC, there are over 100 other compounds that are slowly being discovered to have unique therapeutic effects. If we can produce cannabinoids in yeast, we can precisely control which cannabinoids we produce, thus making research easier for the individual compounds. I use the CRISPR-Cas9 system to integrate Cannabis sativa genes into Yarrowia lipolytica, an oleaginous yeast that may provide particular advantages in producing this class of compounds.

Molecular Sensors

Sensors are a critical component in most circuits. The same holds true for biological circuits. Originally from the plant kingdom, the PYR1-HAB1 system provides a selective and sensitive molecular sensor circuit when tied to a DNA activation and binding domain. The PYR1 component can easily be mutated to accept new ligands. My work has shown that this sensor can be engineered to be selective between very similarly structured cannabinoids as well as have sensitivity down to the nanomolar range.

Enzyme Evolution with Molecular Sensors

Using the PYR1-HAB1 sensors that have been mutated to be selective to particular cannabinoids, I can evolve enzymes in the pathway to have improved kinetics. This tool can very easily be used by others to evolve improved enzymes within a period of weeks without having to scale up production or screen vast amounts of colonies.

Smart Yeast

My lab has developed a CRISPR genome-wide mutagenesis tool that is capable of knocking out or up regulating every gene in the Yarrowia lipolytica genome one at a time. This creates a mutant library that may have individuals that out perform a base cannabinoid producing strain.

If we tie the aforementioned molecular sensors to an auxotrophic marker, we can create “smart yeast” that know what compound they’re producing. With this system, we will easily be able to screen for mutants that outperform wild-type.

You can read more on the genome-wide mutagenesis tool here:

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