Modeling extensive cellular variability in glycolytic rates using multiplexed live-cell data - Summary Glycolysis, the fundamental metabolic process in which glucose is converted to lactate, lies at the core of diabetes and metabolic dysfunction, as well as cancer and immune function. Regulation of glycolytic rate by insulin and other endocrine signals is essential for bodily metabolic homeostasis and also plays important cell-intrinsic roles in regulating cellular proliferation, apoptosis, and differentiation. While there is a long history of quantitative modeling of glycolysis in bulk, regulation at the single-cell level has been explored in much less depth. This lack of understanding makes it impossible to know whether glucose disposal and lactate production are distributed evenly across tissues or are selectively performed by cellular subpopulations. Our lab has made significant progress in single-cell metabolism using multiplexed live-cell measurements for key points of glycolytic flux and regulation, including fructose 1,6-bisphosphate (FBP), NADH/NAD+, ADP/ATP, and kinase activities of AKT, AMPK, and mTOR. Our preliminary data in epithelial, muscle, and liver cell lines indicate an extensive degree of glycolytic heterogeneity and motivate our overall hypothesis that a small number of live-cell measurements can adequately constrain mathematical models of the glycolytic rate distributions. Specifically, we hypothesize that dual measurements of FBP and NADH/NAD+ ratio will provide strong modeling constraints that will enable the distribution of single-cell glucose disposal and lactate production rates. We further hypothesize that signaling by the AKT/AMPK/mTOR network links glycolysis rates to protein synthesis rates to create time-dependent variation and metabolic microenvironments that affect cellular processes including cell death and differentiation. In this project, we will 1) use multiplexed live-cell measurements to constrain models of single-cell glycolytic distributions and identify optimal sets of observables; 2) Measure the single-cell linkage of glycolysis and protein synthesis rates via the AKT, AMPK, and mTOR activities, and 3) create an integrated model of glycolytic flux and signaling network regulation that is currently lacking in the field. The computational models generated in these aims will fill an important gap, enabling an understanding of how glycolytic flux acts as a key information-carrying process integrated with signaling network activity. These models will make it possible to predict how cellular and tissue- level metabolism are affected by the many pharmacological signaling modulators for PI3K, AKT, mTOR, and AMPK now available. We will also gain a greater understanding of how individual cell glycolysis rates participate in cell-intrinsic processes including cell proliferation, death, and differentiation, which are central in diabetes, cancer and other diseases.
