Dr. Lai Hong Wong is a senior research fellow working in the laboratory of Prof. Douglas Fowler and Prof. Maitreya Dunham in the Department of Genome Sciences at the University of Washington. Dr. Wong is interested in leveraging yeast genetics to explore the genetic determinants of drug metabolism that are implicated in adverse drug reactions in humans. We sat down with Dr. Wong to discuss her research.

What is an adverse drug reaction?

Adverse drug reactions (ADRs) are unwanted or undesired reactions that occur as a consequence of taking a specific drug. This can include nausea and vomiting, or more serious reactions, such as liver damage and hemorrhages. ADRs occur due to differences in drug metabolism between individuals, which in turn can cause individual-specific responses. At the moment, it’s difficult to predict when a patient will exhibit an ADR, and it’s therefore difficult to prevent.

How does this relate to your work on cytochrome P450 enzymes?

Cytochrome P450 (CYP) enzymes are a large family of enzymes encoded by 57 functional genes in humans. They have evolved over time to catalyze various reactions from the ability to break down endogenous signalling molecules to the ability to detoxify xenobiotics. Within this family, there is a very specific group that is involved in drug metabolism, and this is the family that I’m interested in studying.

How do you plan to study CYPs and their relationship to ADRs?

The main focus of my project is to apply new technologies to help predict individuals that may experience ADRs. Since CYPs are involved in drug biotransformation and clearance from our bodies, it makes sense that genetic variation in these enzymes could result in various phenotypes depending on whether the variation results in a poor metabolizer or a rapid metabolizer.

In the past, people have tried different methods to characterize these variants and their effects on drug metabolism. This is a huge undertaking considering the number of enzymes in the family that participate in drug metabolism, and the fact that dozens to hundreds of polymorphisms can exist in each CYP enzyme. Furthermore, in order to characterize them in a way that helps clinicians make informative decisions, the variants need to be characterized in a systematic, standardized and quantitative way. This is what I’m trying to do.

What is your strategy to do this?

My strategy is to engineer and express a library of CYP missense variants in S. cerevisiae budding yeast, and use them in an assay I’ve developed to measure function. The assay takes advantage of a covalent-based CYP-directed probe. The probe can be oxidized by the CYP enzyme, forming a reactive intermediate, which then forms an adduct with the protein. The adducts accumulate within cells, so if we label the probe with a fluorophore, we can use fluorescence as a readout for protein activity. So using a combination of yeast genetics, fluorescence chemistry, FACS analysis, and deep sequencing, we have the power to tease apart all the functional consequences of CYP variants.

Why did you choose to do this experiment in yeast rather than in a mammalian system?

That’s a great question! When you study budding yeast, especially in drug discovery, you always have to deal with the skeptics. But the great thing about working with yeast is that there are really powerful genetic tools at your disposal. Plus, in the case of drug metabolizing CYPs, yeast don’t express any endogenous proteins that perform their function, so humanized yeast can work well in isolating their function. Also, CYPs are heme-regulated proteins, and the heme biosynthesis pathway is very well conserved from simple organisms like yeast all the way to humans. So overall budding yeast is a very good recombinant CYP model and provides a eukaryotic cellular environment to probe specific CYP gene function in the absence of other CYP genes.

What is the next step for this project?

I’m about to begin one of the most exciting stages of this project. I just finished engineering a library made of all possible ~10,000 missense variants, which was a huge effort. To get that sort of coverage we had to do a lot of validation just to make sure the library was actually complete. I’m now working on linking all these variants to barcodes, which we can use to identify the individual variants later on in the experiment. I’m also validating the functional assay, so that we can begin assaying once the validations on the barcoded library are complete. I’m very excited for the next 3 months, because we will start collecting preliminary data on the variants.

Once you’ve determined the functional consequence of all these variants, do you plan to validate the results by testing them against a specific drug?

Absolutely. My project is focused on the most polymorphic CYP, CYP2D6, which metabolizes approximately 25% of drugs in current use. Which drugs I can test will depend on whether or not they have a direct readout that I can use. The first drug I plan to test is the breast cancer drug tamoxifen, which is metabolized by several CYPs, including CYP2D6. Importantly, the drug also causes a growth defect in yeast when metabolized by CYP2D6. Therefore, unlike the fluorescence assay that will allow us to assess the general function of variants on a surrogate  probe, we can specifically test the effects of these variants on tamoxifen metabolism using growth as a read out. We’re hoping to look at other gene-drug pairs as well, but it will depend on whether a growth phenotype exists that can be exploited.

What type of impact are you hoping this research has?

This study will hopefully be helpful for the pharmacogenomics discovery field, since, for the first time, it will provide quantitative characterization of how every possible missense variant of a CYP, including common and rare variants, affect drug metabolism. This will be particularly useful because we plan to standardize these effects. So clinicians and other medical researchers can use this information to tailor drug therapy in terms of both drug selection and dose, while minimizing ADRs. Furthermore, we’ll also be providing basic knowledge of how CYPs behave in a given drug environment. Overall it will provide a lot of useful information, and will hopefully help rationalize personalized medicine.

Thank you for taking the time to discuss your research with us, Dr. Wong!