The LIPID MAPS Consortium (www.lipidmaps. org) is developing comprehensive procedures for identifying all lipids of the macrophage, following activation by endotoxin. The goal is to quantify temporal and spatial changes in lipids that occur with cellular metabolism and to develop bioinformatic approaches that establish dynamic lipid networks. To achieve these aims, an endotoxin of the highest possible analytical specification is crucial. We now report a large-scale preparation of 3-deoxy-D-manno-octulosonic acid (Kdo) 2 -Lipid A, a nearly homogeneous Re lipopolysaccharide (LPS) sub-structure with endotoxin activity equal to LPS. Kdo 2 -Lipid A was extracted from 2 kg cell paste of a heptose-deficient Escherichia coli mutant. It was purified by chromatography on silica, DEAE-cellulose, and C18 reverse-phase resin. Structure and purity were evaluated by electrospray ionization/mass spectrometry, liquid chromatography/mass spectrometry and 1 H-NMR. Its bioactivity was compared with LPS in RAW 264.7 cells and bone marrow macrophages from wild-type and toll-like receptor 4 (TLR-4)-deficient mice. Cytokine and eicosanoid production, in conjunction with gene expression profiling, were employed as readouts. Kdo 2 -Lipid A is comparable to LPS by these criteria. Its activity is reduced by . The LIPID MAPS consortium is developing quantitative methods for evaluating the composition, biosynthesis, and function of all macrophage lipids (1). These amphipathic substances not only are structural components of biological membranes but also play important roles in the pathophysiology of inflammation, atherosclerosis, and growth control. Additional lipid functions should emerge from the comprehensive analysis of macrophage lipids. Electrospray ionization/mass spectrometry (ESI/MS) (2, 3), coupled with prefractionation methods like reversephase liquid chromatography (LC), is being applied systematically to set the stage for the seamless integration of lipid metabolism into the broader fields of genomics, proteomics, and systems biology. To facilitate this endeavor, LIPID MAPS has introduced a new comprehensive classification system for biological lipids, amenable to computer-based data processing and substructure comparison (4). The eight LIPID MAPS categories are 1) fatty acyls, 2) glycerolipids, 3) glycerophospholipids, 4) sphingolipids, 5) sterol lipids, 6) prenol lipids, 7) saccharolipids,

Eicosanoids constitute a large class of biologically active arachidonic acid (AA) metabolites that play important roles in numerous physiological processes. Eicosanoids are produced by several distinct routes, including the cyclooxygenase, lipoxygenase, and P450 enzymatic pathways, as well as by nonenzymatic processes. In order to completely understand the eicosanoid response of a cell or tissue to a given stimulus, measuring the complete profile of eicosanoids produced is important. Since the eicosanoids are products of a single species, AA, and represent, for the most part, the addition of various oxygen species, the hundreds of eicosanoids have very similar structures, chemistries, and physical properties. The identification and quantitation of all eicosanoids in a single biological sample are a challenging task, one that high-performance liquid chromatography-mass spectrometry (LC-MS) is well suited to handle. We have developed a LC-MS/MS procedure for isolating, identifying, and quantitating a broad spectrum of eicosanoids in a single biological sample. We currently can measure over 60 eicosanoids in a 16-min LC-MS/MS analysis. Our method employs stable isotope dilution internal standards to quantitate these specific eicosanoids. In the course of setting up the LC-MS system, we have established a library that includes relative chromatographic retention times and tandem mass spectrometry data for the most common eicosanoids. This library is available to the scientific community on the website www.lipidmaps.org.

Arachidonic acid is released by phospholipase A 2 and converted into hundreds of distinct bioactive mediators by a variety of cyclooxygenases (COX), lipoxygenases (LO), and cytochrome P450s. Because of the size and diversity of the eicosanoid class of signaling molecules produced, a thorough and systematic investigation of these biological processes requires the simultaneous quantitation of a large number of eicosanoids in a single analysis. We have developed a robust liquid chromatography/tandem mass spectrometry method that can identify and quantitate over 60 different eicosanoids in a single analysis, and we applied it to agoniststimulated RAW264.7 murine macrophages. Fifteen different eicosanoids produced through COX and 5-LO were detected either intracellularly or in the media following stimulation with 16 different agonists of Toll-like receptors (TLR), G protein-coupled receptors, and purinergic receptors. No significant differences in the COX metabolite profiles were detected using the different agonists; however, we determined that only agonists creating a sustained Ca 2؉ influx were capable of activating the 5-LO pathway in these cells. Synergy between Ca 2؉ and TLR pathways was detected and discovered to be independent of NF-B-induced protein synthesis. This demonstrates that TLR induction of protein synthesis and priming for enhanced phospholipase A 2 -mediated eicosanoid production work through two distinct pathways.

Arachidonic acid is released and converted into hundreds of different bioactive mediators by a variety of cyclooxygenases (COX), lipoxygenases (LO) and cytochrome P450s (CYP). Due to the size and diversity of the eicosanoid class of signaling molecules produced, a thorough and systematic investigation of these biological processes requires the simultaneous quantitation of a large number of eicosanoids in a single analysis. We have developed a LC/MS/MS method that can identify and quantitate over 60 eicosanoids with standards in a single analysis, and applied it to RAW264.7 murine macrophage cells. Changes in the metabolic profile following stimulation with 21 different agonist conditions were correlated to gene expression using microarray analysis, showing the interplay between genomics and metabolomics. This approach allows us to investigate potential novel eicosanoid signaling networks with an array of different agonists and correlate them with gene induction and metabolite profiles. This work was supported by the LIPID MAPS Large Scale CollaborativebGrant GM‐069338 from the National Institutes of Health.

No abstract