Our Research
Mechanisms of protein-metabolite co-regulation in health and disease
The human genome encodes over 20,000 protein-coding genes, yet over the past two centuries, life science publications have primarily focused on ~6,000 well-studied proteins. While some proteins, like p53, have been the subject of over ten thousand papers, a significant portion of the proteome remains understudied, with the functions of many proteins yet to be discovered.
We develop mass spectrometry (MS)-based approaches that leverage genetically diverse population models to study co-variations among proteins, metabolites, and metabolic phenotypes. These approaches allow us to understand the roles of orphan and understudied proteins in regulating cellular and systemic metabolism. Currently, we are interested in developing technologies to investigate how proteins and protein families regulate metabolites on a proteome-wide scale and in vivo; and how metabolic outputs, in turn, modulate protein function to maintain nutrient and energy homeostasis. We aim to mechanistically characterize molecular targets in metabolic disease and cancer, and to develop translational therapeutics.
Representative publication:
Metabolic regulation via protein post-translational modifications (PTMs)
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 to a persistent absence of methods that quantify PTMs on a large scale. We are interested in understanding the roles of protein glycosylation, ubiquitination, and cysteine redox modifications in aging, metabolic disease, and cancer. To address these questions, we develop chemoproteomics methods to generate systems-level overviews and employ data science to prioritize molecular targets for mechanistic characterization. For targets with translational potential, we use activity-based proteome profiling (ABPP) to identify small molecules capable of modulating target function, paving the way for therapeutic developments.
Representative publications:
