|Ph.D Student||Ahn Eunyong|
|Subject||Characterization of Cellular Metabolism throughout the|
Cell Cycle in Cancer: An Integrated Experimental-
|Department||Department of Computer Science||Supervisor||Professor Tomer Shlomi|
Cell cycle progression is tightly interlinked with cellular metabolism. The availability of sufficient metabolic nutrients and intracellular energy status control the ability of cells to enter and progress through cell cycle. While the cell cycle machinery was found to regulate the concentration of key metabolic enzymes, an understanding of how the actual rate of metabolic reactions and pathway (i.e. metabolic flux) change throughout the cell cycle is still fundamentally missing. Here, we developed a temporal-fluxomics approach to derive a comprehensive and quantitative view of alterations in metabolic fluxes throughout the mammalian cell cycle. This is achieved by combining pulse-chase LC-MS based isotope tracing in synchronized cell populations with computational deconvolution and metabolic flux modelling. Specifically, we synchronized HeLa cells and applied high-throughput LC-MS based targeted metabolomics analysis to synchronized cell populations throughout two complete cell cycles. As cell synchronization is gradually lost with time due to inherent non-genetic cell-to-cell variability, the distribution of cell cycle phases in the synchronized cell population becomes similar to that of non-synchronized cells with time. To account for the loss of synchrony and to precisely quantify oscillations in metabolite levels, we employed “computational synchronization”. Inferring the dynamics of metabolite concentrations throughout the cell cycle (rather than that of metabolite abundances) further required estimates of the dynamics of cell volume throughout the cell cycle. Finally, a variant of Kinetic Flux Profiling (KFP) was employed to infer metabolic flux dynamics throughput the cell cycle.
Applied to HeLa cells, we derived a first comprehensive and quantitative view of metabolic flux oscillations at a high temporal resolution in central metabolism throughout the cell cycle of human cells, showing complementary oscillations between glucose and glutamine-derived flux in the TCA cycle throughout the cell cycle: oxidation of glucose-derived flux peaks in late G1 phase while oxidative and reductive glutamine metabolism dominates S phase. These complementary flux oscillations maintain a constant production rate of reducing equivalents and oxidative phosphorylation flux throughout the cell cycle. The shift from glucose to glutamine oxidation in S phase plays an important role in cell cycle progression and cell proliferation. After treating HeLa cells with the PDK inhibitor DCA, the oscillations in glucose flux into TCA cycle were eliminated, suggesting that cell cycle specific regulation of PDH activity may be involved in regulating these flux oscillations.
Understanding the metabolic adaptation of cells to tumorigenic mutations is a central goal of cancer metabolic research. Considering that tumorigenic mutations typically alter cell cycle progression, flux alterations observed at a cell population level may merely reflect a change in the distribution of cell-cycle phases in the population (due to cells in different phases having different metabolic fluxes). Hence, the presented temporal-fluxomics approach will enable to revisit our understanding of oncogene-induced metabolic alterations, disentangling population level artifacts from directly regulated flux alterations with important tumorigenic role and revealing potential targets for therapy.