Our Research
Uncovering molecular mechanisms of protein-metabolite co-regulation
The human genome encodes over 20,000 protein-coding genes, yet over the past two centuries, life science research has primarily focused on only ~6,000–7,000 well-studied proteins. A large portion of the proteome therefore remains understudied, with the functions of many proteins still unknown.
Our work centers on developing mass spectrometry (MS)-based technologies to uncover the roles of orphan and understudied proteins in regulating cellular and systemic metabolism. We apply MS and machine learning approaches to investigate how proteins regulate metabolites on a proteome-wide scale and in vivo, and how metabolic cues in turn modulate protein abundance and function to maintain metabolic homeostasis. Using this approach, we deorphanized Leucine-Rich Repeats Containing Protein 58 (LRRC58) and defined its role in controlling cysteine metabolism. We found that LRRC58 functions as the substrate adaptor of an E3 ubiquitin ligase that mediates proteasomal degradation of CDO1, the rate-limiting enzyme that channels cysteine into the catabolic pathway toward hypotaurine and taurine. Moreover, we discovered that cysteine itself serves as the molecular signal that turns on and off LRRC58-mediated CDO1 degradation. In this way, the LRRC58-CDO1 partnership is able to sense cellular cysteine levels and maintain cysteine homeostasis.
Currently, we are focused on understanding how metabolism is rewired during aging and cancer, with the goal of identifying therapeutically actionable molecular targets to extend healthspan and combat cancer.
Representative publications:
Mammalian cells and tissues control distinct physiological processes despite sharing substantially overlapping transcriptomes and proteomes. Much of this specialized physiology is governed by protein post-translational modifications (PTMs), which serve as a major mechanism by which cells sense metabolic cues, fine-tune protein function, and elicit adaptive responses.
Despite the widely appreciated importance of PTMs in regulating mammalian physiology and disease, comprehensive and mechanistic interrogation remains lacking due lack of methods to quantify PTMs at scale. We are interested in understanding the roles of PTMs in aging, metabolic disease, and cancer. We develop chemoproteomics methods to generate systems-level overviews and use data science to prioritize molecular targets for mechanistic characterization. For targets with high translational potential, we leverage activity-based proteome profiling (ABPP) to identify chemical leads and pave the way for development of therapeutics.
Currently, we are developing chemoproteomic methods to design covalent inhibitors or degrader molecules that selectively target specific amino acid residues on cancer-driver proteins. In parallel, we are performing large-scale profiling of protein-ligand interactions to generate high-resolution datasets to enable AI-based rational drug discovery.
Representative publications:
Defining the biological roles of protein post-translational modifications
We are currently pursuing the following directions:
1. Developing mass spectrometry and machine learning approaches to elucidate molecular mechanisms of metabolic rewiring in cancer and aging.
2. Designing activity-based proteome profiling (ABPP) strategies to guide the development of chemical leads that target undrugged proteins or proteins prone to drug resistance.
3. Combining mass spectrometry with genetic perturbations to mechanistically define protein functions at scale.
4. Creating automation strategies for large-scale proteomics and metabolomics.
5. Defining the role of protein LRRC58 in physiology and disease, and developing chemical leads to target LRRC58 for therapeutic benefits.