Journal of Lipid ResearchImmunologyPeer-reviewed journal article
Resolving vs. Non-resolving Sphingolipid Dynamics During Macrophage Activation: A Time-resolved Metabolic Analysis
Abstract
Sphingolipids are increasingly recognized as critical regulators of inflammation and cell fate decisions, with metabolites such as ceramide and sphingosine 1{square}phosphate exerting contrasting effects on cell survival and proliferation. In macrophages, this balance is especially important, given their central role in host defense, pathogenesis and wound healing. Here, we present a time{square}resolved model of sphingolipid metabolism in RAW 264.7 macrophages stimulated with KdO{square}-Lipid A. By integrating measured metabolite concentrations with dynamic flux estimation and established enzyme kinetics, we systematically map dynamic changes in the sphingolipid network during inflammation. Our results reveal a three{square}phase pattern of sphingolipid remodeling that correlates with distinct functional states of the cell. Moreover, metabolites can be classified into "resolving" or "non{square}resolving" lipids based on whether they return to basal levels or remain dysregulated through the later phases of the inflammatory response. This partitioning suggests that targeted modulation of specific metabolic nodes may influence the resolution of inflammation. Importantly, our computational approach can assist in the rational design of experimental studies by pinpointing putative drug targets with maximal impact on sphingolipid homeostasis. Such targeted interventions may prevent the pathological amplification of inflammatory signals without globally suppressing essential sphingolipid functions. These findings highlight the utility of an integrative systems{square}level analysis for elucidating sphingolipid dynamics in macrophages and underscore its potential to guide therapeutic strategies against conditions involving dysregulated inflammation.
- organism: mouse
- assay: metabolomics
- research focus: host-pathogen & immune response
- approach: statistical model
- Citations
- 3
- FWCI
- 0.83
- Field percentile
- top 31%
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