Postdoctoral work: Gygi Lab, Harvard Cell Biology
Traditionally, targeted proteomics is labor- and time-intensive and has limited success rates and sample throughput. In the Gygi Lab, I am solving these problems with new computational tools and applying the resulting technology to high-throughput studies of drug-protein interactions and intracellular signaling pathways.
The figure on the right is from the Gygi Lab's 2023 paper describing GoDig, a new method for targeting whole pathways of proteins with tandem mass tags (TMT) for high sample throughput. I have recently increased the success rates of GoDig to the point where single-peptide sites of interest, such as proteolytic cleavage sites, phosphorylation sites, or reactive cysteines can be reliably and sensitively quantified. I am using AI to develop methods that do not require the use of data libraries, making targeted proteomics as easy and reliable as untargeted proteomics.
Yu, Q.; Liu, X.; Keller, M. P.; Navarrete-Perea, J.; Zhang, T.; Fu, S.; Vaites, L. P.; Shuken, S. R.; et al. “Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression.” Nature Comm. 2023, 14, 555.