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Computational lipidomics: Mathematical modeling of a signaling pathway in RAW 264.7 cells
Author(s) -
Brown Alex
Publication year - 2006
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.20.5.a1472
Subject(s) - diacylglycerol kinase , phosphatidic acid , lipidomics , lipid signaling , second messenger system , signal transduction , microbiology and biotechnology , 2 arachidonoylglycerol , cell signaling , biochemistry , chemistry , effector , calcium signaling , phosphatidylinositol , lysophosphatidic acid , biology , computational biology , protein kinase c , receptor , phospholipid , cannabinoid receptor , membrane , agonist
A goal of computational Lipidomics is the identification of the glycerophospholipids in a mammalian cell. We have constructed a mathematical model for the uridine 5′‐diphosphate (UDP) signaling pathway in the RAW 264.7 macrophage. This mathematical model incorporates modules for: (i) the ligand interaction with the P2Y 6 receptor; (ii) the subsequent G‐protein cascade; (iii) the activation of effector enzymes including phospholipase C (PLC), diacylglycerol kinase (DGK), and several forms of phosphatidylinositol kinase (PI4K, PI5K). In addition, small molecule dynamics for calcium, IP 3 , and PIPn species are either modeled or used as functional inputs to provide a comprehensive description of the signaling dynamics. Our model focuses on the regulated production of diacylglycerol (DAG) and phosphatidic acid (PA) as important lipid second messengers and on substrate‐product relationships in macrophages. This model is contrasted with other signaling pathways of interest to illustrate the ability to identify differences in network signaling circuits using a mass spectrometry based lipid analysis approach.