Our lab aims to achieve a quantitative, comprehensive understanding of cellular metabolism. Our motivation for studying metabolism is two-fold. From a basic science perspective, the molecular connections involved in metabolism are the best understood of any major biochemical network. Accordingly, metabolism provides a unique opportunity for quantitative analysis. From a practical perspective, derangements of metabolism are a major cause of disease, and small molecules that inhibit metabolism are the basis of many important pharmaceuticals. Accordingly, systems-level analysis of metabolism is likely to yield discoveries of medical significance.
A major barrier to understanding metabolism has been lack of appropriate tools. Our lab has developed methods for measuring a wide range of cellular metabolites using state-of-the-art mass spectrometry technology. We have innovated approaches to quantitating metabolic fluxes by interpreting isotope-labeling data within a rigorous chemical-kinetic framework. These analytical tools enable us to effectively re-examine long-standing and fundamental questions regarding regulation of metabolism: How are metabolite concentrations and fluxes controlled? How do microbes adapt to changing nutrient availability? How do anti-metabolite drugs work? In this vein, we have identified a conserved metabolomic response of E. coli and yeast to nutrient deprivation (Brauer et al., 2006), and are beginning to figure out (and quantitatively model) the underlying regulatory circuitry. Through such efforts, we are identifying novel features of cellular metabolic regulation. Among these is a previously unrecognized cascade of enzyme inhibition triggered by the antibiotic trimethoprim (Kwon et al., 2008). A future objective is to understand coordination across different nutrient systems, leading to the development of predictive dynamic models of the entirety of core metabolism. Such models, in addition to basic science utility, should have value for optimizing biofuel production.
These analytical tools enable us to effectively re-examine long-standing and fundamental questions regarding regulation of metabolism: How are metabolite concentrations and fluxes controlled? How do microbes adapt to changing nutrient availability? How do cancer cells survive in the hypoxic environment of a tumor? In this vein, we have developed predictive, dynamic models of E. coli nitrogen metabolism (Yuan et al., 2009). Through such efforts, we are identifying key features of cellular metabolic regulation, such as competition among metabolites for enzyme active sites (Bennett et al., 2009). A future objective is to understand coordination across different nutrient systems, leading to quantitative models of the entirety of core metabolism. Such models will incorporate not just metabolite data, but also data on enzyme transcription, covalent modification, and localization. In addition to basic science utility, they will enable optimization of biofuel production.
Metabolomic tools are also opening new avenues of investigation, such as investigation into the metabolism of parasite-infected human cells. We have studied plasmodium-infected red blood cells and cytomegalovirus-infected fibroblasts. In the latter case, we identified a dramatic up-regulation of fatty acid biosynthesis in response to viral infection. Inhibition of this pathway blocks viral replication, thereby suggesting a new strategy for antiviral therapy (Munger et al., 2008). We now aim to understand how and why cytomegalovirus hijacks metabolism and whether other viruses act similarly. We also aim to identify new therapeutics based on these discoveries.
Ongoing research efforts of our fall into the following general categories:
All projects involve a mix of biological experiments, metabolomics, and computation.
