Development and Application of FASA, a Model for Quantifying Fatty Acid Metabolism Using Stable Isotope Labeling

Joseph P. Argus; Moses Q. Wilks; Quan D. Zhou; Wei Yuan Hsieh; Elvira Khialeeva; Xen Ping Hoi; Viet Bui; Shili Xu; Amy K. Yu; Eric S. Wang; Harvey R. Herschman; Kevin J. Williams; Steven J. Bensinger

Development and Application of FASA, a Model for Quantifying Fatty Acid Metabolism Using Stable Isotope Labeling

2018

Summary: It is well understood that fatty acids can be synthesized, imported, and modified to meet requisite demands in cells. However, following the movement of fatty acids through the multiplicity of these metabolic steps has remained difficult. To better address this problem, we developed Fatty Acid Source Analysis (FASA), a model that defines the contribution of synthesis, import, and elongation pathways to fatty acid homeostasis in saturated, monounsaturated, and polyunsaturated fatty acid pools. Application of FASA demonstrated that elongation can be a major contributor to cellular fatty acid content and showed that distinct pro-inflammatory stimuli (e.g., Toll-like receptors 2, 3, or 4) specifically reprogram homeostasis of fatty acids by differential utilization of synthetic and elongation pathways in macrophages. In sum, this modeling approach significantly advances our ability to interrogate cellular fatty acid metabolism and provides insight into how cells dynamically reshape their lipidomes in response to metabolic or inflammatory signals. : Argus et al. developed Fatty Acid Source Analysis (FASA), a model that quantifies cellular fatty acid synthesis, elongation, and import. FASA is used to demonstrate that elongation can be a major contributor to cellular fatty acid content and that different stimuli reprogram macrophage fatty acid elongation pathways in distinct ways. Keywords: fatty acid homeostasis, fatty acid modeling, stable isotope labeling

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