Modeling of eicosanoid fluxes reveals functional coupling between cyclooxygenases and terminal synthases

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.

Figure 1

Lipidomics and transcriptomics analysis. (A) BMDM were pretreated with or without KLA for 4 h, and then stimulated with or without ATP. Media and cells were collected for lipidomic and transcriptomic analysis. The representative lipidomic (B) and transcriptomic (C) data for the AA metabolic network are shown as heat maps based on primary data available online (http://www.lipidmaps.org; H.A. Brown, unpublished). The ratios of ATP-treated (nonprimed)/control (Ctrl) and KLA-primed-ATP-treated (KLA-primed)/Ctrl at the corresponding time points were normalized using log transformations. The ratios of AUC of eicosanoid profiles in KLA-primed/nonprimed are shown on the right side of the heat maps.

Figure 2

Computational simulation of eicosanoid profile in ATP-stimulated BMDM (for dataset A). (A) Simplified COX (left side) and LOX (right side) pathway maps are shown. (Rectangles) Enzymes; (ellipses) lipid metabolites. (Shaded) Unmeasured metabolites. (Arrows) Enzymatic and nonenzymatic reactions. (∅) Additional metabolic pathways including degradation. The simulation results for COX (B) and LOX (C) metabolites are shown. The experimental data (Exp) for ATP-treated (Trt) and control (Ctrl) represent mean ± SE (n = 3). The simulation results (Fit) are shown (solid and shaded curves, respectively) for Trt and Ctrl.

Figure 3

Computational prediction of the eicosanoid profile in KLA-primed ATP-stimulated BMDM (for dataset B). The predicted results for COX (A) and LOX (B) metabolites are shown. The experimental data (Exp) for KLA-primed ATP-treated (Trt) and control (Ctrl) represent mean ± SE (n = 3). The simulation results (Fit) are shown (solid and shaded curves, respectively) for Trt and Ctrl.

Figure 4

PGH₂-divided model. (A) A modified COX pathway is shown. (Rectangles) Enzymes; (ellipses) lipid metabolites. C1PGH₂, C2PGH₂, and 15-keto-PGD₂ are unmeasured metabolites. (Arrows) Enzymatic and nonenzymatic reactions. (∅) Other metabolic pathways including degradation. (B) Kinetic parameter values in the PGH₂-divided model (pink or light-gray, k_CPn) and the corresponding values in the single-PGH₂ model (dark-gray, k_Cn) are compared to validate the PGH₂-divided model. (C) Fluxes are computed by using calculated parameters. COX-1 and COX-2-mediated fluxes in ATP-stimulated (nonprimed) and KLA-primed ATP-stimulated (KLA-primed) BMDM are shown (as blue/dark-gray and green/light-gray lines, respectively). (Dotted lines) Simulated fluxes in control cells. (D) The inhibitory effects of NSAIDs are simulated by changing the calculated parameters k_CP1, k_CP2, k_CP'1, and k_CP'2. The efficiencies of NSAIDs are calculated as a ratio of AUC between nontreated and NSAID-treated cells. (E) PGD₂ and PGE₂ were quantified in the presence or absence of COX inhibitors at 20 h after ATP stimulation. The eicosanoid levels were normalized using control levels. (Bars) Mean ± SE (n = 6 from two independent experiments). ^∗p < 0.05 versus Ctrl, by Kruskal-Wallis test followed by Dunn's multiple comparison test. To see this figure in color, go online.