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Probing Cell Metabolism Using Isotope Tracers and Metabolic Flux Analysis

presented by

Christian Metallo
Assistant Professor of Bioengineering
University of California, San Diego (UCSD)

October 17, 2013

TSRI Auditorium


Background:

Christian Metallo joined the University of California, San Diego in 2011 and is currently an assistant professor in the Department of Bioengineering. He received his bachelor's in chemical engineering from the University of Pennsylvania in 2000 before joining Merck Research Laboratories to conduct bioprocess engineering research. He received his Ph.D. from the University of Wisconsin-Madison Department of Chemical and Biological Engineering in 2008 and was an American Cancer Society Postdoctoral Fellow in Chemical Engineering at the Massachusetts Institute of Technology. Christian was the recipient of the Biomedical Engineering Society Rita Schaffer Young Investigator Award in 2012 and is a 2013 Searle Scholar.

Abstract:

Metabolism is central to virtually all cellular functions and contributes diseases that include cancer, obesity, and type 2 diabetes. A detailed understanding of how metabolic pathways are regulated in these contexts requires data beyond the abundance and identity of compounds within the metabolome. Quantitative information describing the flow of metabolites through biochemical networks provides critical insights into how different nutrients contribute to energy metabolism and biosynthesis. To this end we apply stable isotope tracers, mass spectrometry, and metabolic flux analysis to study central metabolism in mammalian cells. Using these approaches we have characterized how proliferating and differentiated cells regulate flux of glucose and amino acids into mitochondria for biosynthesis. We have also applied MFA to cancer cells with specific metabolic defects to identify enzyme targets that selectively inhibit growth. Finally, we are developing tracer-based methods to probe the pentose phosphate pathway and redox metabolism in the cytosol and mitochondria. The application of systems-level approaches to these models greatly improves our ability to characterize intracellular metabolic processes, providing a mechanistic understanding of cellular physiology and metabolic function.

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