Abstract
Eicosanoids, including prostaglandins (PG) and leukotrienes, are lipid mediators derived from arachidonic acid. A quantitative and biochemical level understanding of eicosanoid metabolism would aid in understanding the mechanisms that govern inflammatory processes. Here, we present a combined experimental and computational approach to understanding the biochemical basis of eicosanoid metabolism in macrophages. Lipidomic and transcriptomic measurements and analyses reveal temporal and dynamic changes of the eicosanoid metabolic network in mouse bone marrow-derived macrophages (BMDM) upon stimulation of the Toll-like receptor 4 with Kdo2-Lipid A (KLA) and stimulation of the P2X7 purinergic receptor with adenosine 5'-triphosphate. Kinetic models were developed for the cyclooxygenase (COX) and lipoxygenase branches of arachidonic acid metabolism, and then the rate constants were estimated with a data set from ATP-stimulated BMDM, using a two-step matrix-based approach employing a constrained least-squares method followed by nonlinear optimization. The robustness of the model was validated through parametric sensitivity, uncertainty analysis, and predicting an independent dataset from KLA-primed ATP-stimulated BMDM by allowing the parameters to vary within the uncertainty range of the calculated parameters. We analyzed the functional coupling between COX isozymes and terminal enzymes by developing a PGH2-divided model. This provided evidence for the functional coupling between COX-2 and PGE2 synthase, between COX-1/COX-2 and PGD2 synthase, and also between COX-1 and thromboxane A2 synthase. Further, these functional couplings were experimentally validated using COX-1 and COX-2 selective inhibitors. The resulting fluxomics analysis demonstrates that the "multi-omics" systems biology approach can define the complex machinery of eicosanoid networks.