Metabolomics in our lab delves deep into the world of small-molecule intermediates, aiming to unravel the full potential of biochemical pathways. One of our key areas of interest is “zombie” metabolism: the unexpected persistence of enzymatic activity in cell-free extracts long after cells have been broken open. By mapping and quantifying these hidden metabolic networks, we gain insights into how leftover enzymatic cascades can impact protein synthesis, resource consumption, and overall reaction dynamics. This detailed, high-resolution picture of cell-free metabolite profiles empowers us to fine-tune reaction conditions, boost protein yields, and design next-generation cell-free systems that are faster, more efficient, and tailored to meet diverse user needs.
Example Projects
Exploring the Crabtree Effect in Yeast via Metabolomics
The Crabtree (CT) effect is a metabolic phenomenon where yeast perform aerobic fermentation of glucose to ethanol in glucose- and oxygen-rich environments, rather than the expected metabolism of aerobic respiration. Yeast that prefer to ferment in aerobic, high glucose conditions are called CT positive, and yeast species that prefer to respire are called CT negative. Although we know what genes control the onset of the CT effect, how these genes affect metabolism to initiate this response is still unclear. We are utilizing metabolomics analysis to study the CT effect by exploring how individual genes affect yeast fermentation and respiration. Metabolomics allows us to track the changes of individual metabolites that are involved the chemical reactions of metabolism. We are interested in exploring how the deletion of genes involved in the CT effect affect the fermentative and respiratory metabolism of CT-positive and -negative yeast. With this information, we will be able to compare the differences between CT-positive and -negative yeast to better understand how they may have evolved. This project can also aid in a more targeted approached to metabolically engineer these different species for optimal ethanol production. Lastly, this project can provide us with new insights on the CT effect that may be applicable to other organisms, such as cancer, that share a similar metabolism to CT positive yeast.