Mapping the functional landscape of the pharmacogene CYP2D6 in Saccharomyces cerevisiae

Abstract

Pharmacogenes are responsible for metabolizing exogenous substances such as food, pollutants, and drugs. Due to this, genetic variability in pharmacogenes can help determine proper dosing for certain drugs. For instance, if an individual has a decreased-function pharmacogene allele, the standard dose for a certain drug might not be effective and the individual may need a higher dose. CYP2D6 is a pharmacogene responsible for metabolizing about 25% of common drugs, including SSRIs, beta-blockers, and opioids. Specifically, individuals with an ultra-rapid metabolizer CYP2D6 allele are at a greater risk of opioid overdose. However, many of the genetic variants of CYP2D6 have unknown consequences, making it difficult to provide clear guidance to patients and clinicians. My project aims to measure the function of thousands of alleles, both known and yet to be discovered, to address this gap. To begin to understand the functional effects of different CYP2D6 variants, we conducted a deep mutational scan (DMS) of CYP2D6 using click-seq in Saccharomyces cerevisiae. Click-seq uses an activity-based probe to measure enzyme activity–after the activity-based probe reacts with enzymes present in the yeast cells expressing CYP2D6 variants, we introduce a fluorophore that binds to the probe and fluoresces. Fluorescence intensity is then expected to be proportional to the activity of the CYP2D6 enzyme within the yeast cell. Using click-seq, we have obtained function scores for 5,075 of the possible 9,940 missense variants of CYP2D6. Previous assays were only able to characterize 20 missense and frameshift variants as WT-like, decreased-function, and no function, and our scores largely agree with these previous inferences. Additionally, we have started to explore the functional effects of double variants to determine if their effects can be inferred from our previous results on single variants. Since most CYP2D6 alleles in the human population are complex alleles, demonstrating that their activities can be predicted based on their constituent single mutations could significantly enhance clinical decision-making. Investigating how different CYP2D6 variants function in yeast cells will bring us one step closer to being able to successfully use pharmacogenomics to help determine proper dosing for drugs.